{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "# 第四回：文字图例尽眉目\n",
    "\n",
    "学习 [Matplotlib](https://matplotlib.org/stable/index.html) 的 [Figure](https://matplotlib.org/stable/api/figure_api.html#matplotlib.figure.Figure)、[Axes](https://matplotlib.org/stable/api/axes_api.html#matplotlib.axes.Axes)、[Tick](https://matplotlib.org/stable/api/axis_api.html#matplotlib.axis.Tick)、[Legend](https://matplotlib.org/stable/api/legend_api.html#matplotlib.legend.Legend) 上的 文本信息([Text](https://matplotlib.org/stable/api/text_api.html#matplotlib.text.Text)) 绘制。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "| pyplot API | OO API | 描述 |\n",
    "| -------- | -------- | -------- |\n",
    "| [text](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.text.html#matplotlib.pyplot.text)   | [text](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.text.html#matplotlib.axes.Axes.text)   | 添加 [Axes](https://matplotlib.org/stable/api/axes_api.html#matplotlib.axes.Axes) 的文本 |\n",
    "| [annotate](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.annotate.html#matplotlib.pyplot.annotate)     | [annotate](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.annotate.html#matplotlib.axes.Axes.annotate)     | 添加 [Axes](https://matplotlib.org/stable/api/axes_api.html#matplotlib.axes.Axes) 的标注和箭头 |\n",
    "| [xlabel](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xlabel.html#matplotlib.pyplot.xlabel)     |  [set_xlabel](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.set_xlabel.html#matplotlib.axes.Axes.set_xlabel)    | 添加 [Axes](https://matplotlib.org/stable/api/axes_api.html#matplotlib.axes.Axes) 的x轴标签     |\n",
    "| [ylabel](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xlabel.html#matplotlib.pyplot.ylabel)     |  [set_ylabel](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.set_ylabel.html#matplotlib.axes.Axes.set_ylabel)    | 添加 [Axes](https://matplotlib.org/stable/api/axes_api.html#matplotlib.axes.Axes)的 y轴标签     |\n",
    "| [title](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.title.html#matplotlib.pyplot.title)     |  [set_title](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.set_title.html#matplotlib.axes.Axes.set_title)    |  添加 [Axes](https://matplotlib.org/stable/api/axes_api.html#matplotlib.axes.Axes) 的标题  |\n",
    "| [figtext](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.figtext.html#matplotlib.pyplot.figtext)     | [text](https://matplotlib.org/stable/api/figure_api.html#matplotlib.figure.Figure.text)     | 添加 [Figure](https://matplotlib.org/stable/api/figure_api.html#matplotlib.figure.Figure) 的文本     |\n",
    "| [suptitle](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.suptitle.html#matplotlib.pyplot.suptitle)     |  [suptitle](https://matplotlib.org/stable/api/figure_api.html#matplotlib.figure.Figure.suptitle)    |  添加 [Figure](https://matplotlib.org/stable/api/figure_api.html#matplotlib.figure.Figure) 的标题    |\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## 一、Figure和Axes上的文本\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.text\n",
    "\n",
    "1. pyplot API:\n",
    "\n",
    "```python\n",
    "matplotlib.pyplot.text(\n",
    "    x, y,          # float, text的位置\n",
    "    s,             # str, text\n",
    "    fontdict=None, # dict, default: None, 配置text属性\n",
    "    **kwargs)      # text属性. 详细信息见 matplotlib.text.Text\n",
    "return Text        # 创建好的Text实例对象\n",
    "```\n",
    "\n",
    "- 更多详细信息请参考 [Matplotlib Reference](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.text.html#matplotlib.pyplot.text)。\n",
    "\n",
    "2. OO API：\n",
    "\n",
    "```python\n",
    "matplotlib.text.Text(\n",
    "    x=0, y=0,          # float, text的位置\n",
    "    text='',           # str, text\n",
    "    color=None,        # str, text颜色\n",
    "    # text垂直对齐方式, default:'baseline'\n",
    "    # {'center', 'top', 'bottom', 'baseline', 'center_baseline'}\n",
    "    verticalalignment='baseline', \n",
    "    # text水平对齐方式, default:'left'\n",
    "    # {'center', 'right', 'left'}\n",
    "    horizontalalignment='left', \n",
    "    # str, 多行text对齐方式, {'left', 'right', 'center'}\n",
    "    multialignment=None,\n",
    "    # font_manager.FontProperties or str or pathlib.Path, 设置text字体属性\n",
    "    # str解释为FontProperties，pathlib.Path解释为字体文件的绝对路径\n",
    "    fontproperties=None, \n",
    "    rotation=None,     # float, text逆时针旋转角度\n",
    "    linespacing=None,  # float, 设置行间距为字体大小的倍数, default: 1.2\n",
    "    rotation_mode=None,# str, text旋转模式, {None, 'default', 'anchor'}\n",
    "    usetex=None,       # bool or None, 是否使用Tex, default: False\n",
    "    wrap=False,        # bool, text是否换行\n",
    "    transform_rotates_text=False, # bool, 旋转是否影响文本方向\n",
    "    parse_math=True,   # bool, 是否解析mathtext\n",
    "    **kwargs)\n",
    "```\n",
    "- 更多详细信息请参考 [Matplotlib Reference](https://matplotlib.org/stable/api/text_api.html#matplotlib.text.Text)。\n",
    "\n",
    "字体的默认配置信息在 `Lib\\site-packages\\matplotlib\\mpl-data\\matplotlibrc` 文件里并被保存在 `class matplotlib.RcParams` 中。如：\n",
    "\n",
    "```plain\n",
    "font.family:  sans-serif\n",
    "font.style:   normal\n",
    "font.variant: normal\n",
    "font.weight:  normal\n",
    "font.stretch: normal\n",
    "font.size:    10.0\n",
    "```\n",
    "\n",
    "我们可以通过修改 `class matplotlib.RcParams` 的属性 或 修改 `matplotlibrc` 配置文件这两种方式修改默认属性。\n",
    "\n",
    "- 更多详细信息请参考 [class matplotlib.RcParams](https://matplotlib.org/stable/api/matplotlib_configuration_api.html#matplotlib.RcParams) 和 [Customizing Matplotlib with style sheets and rcParams](https://matplotlib.org/stable/tutorials/introductory/customizing.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "另外在 [matplotlib.font_manager](https://matplotlib.org/stable/api/font_manager_api.html) 模块下有三个类：\n",
    "\n",
    "<img src=\"https://img-blog.csdnimg.cn/20201120143907452.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3NpbmF0XzMyNTcwMTQx,size_16,color_FFFFFF,t_70#pic_center\" style=\"zoom:0.75;\">\n",
    "\n",
    "\n",
    "参考博客: [一文彻底解决 matplotlib 中的字体管理](https://blog.csdn.net/sinat_32570141/article/details/109848383)\n",
    "\n",
    "其中最常用的是 `FontProperties` 类。\n",
    "\n",
    "- [FontProperties](https://matplotlib.org/stable/api/font_manager_api.html#matplotlib.font_manager.FontProperties)\n",
    "\n",
    "```python\n",
    "class matplotlib.font_manager.FontProperties(\n",
    "    # str, 字体种类, default: 'sans-serif'\n",
    "    # 'sans-serif', 'serif', 'cursive', 'fantasy', or 'monospace'\n",
    "    # 详细信息参考如下网址: \n",
    "    # https://www.runoob.com/css/css-font.html\n",
    "    # https://developer.mozilla.org/zh-CN/docs/Learn/CSS/Styling_text/Fundamentals\n",
    "    family=None, \n",
    "    \n",
    "    # str, 字体样式, default: 'normal'\n",
    "    # {'normal', 'italic', 'oblique'}\n",
    "    # 'italic' 是指斜体字体，而 'oblique' 是倾斜的文字, 二者有区别\n",
    "    style=None, \n",
    "    variant=None,  # str, 字体异体, 'normal' (default) or 'small-caps'\n",
    "    \n",
    "    # str or int(0-1000), 字体粗细, default: 'normal' \n",
    "    # 'ultralight', 'light', 'normal', 'regular', 'book', \n",
    "    # 'medium', 'roman', 'semibold', 'demibold', 'demi', \n",
    "    # 'bold', 'heavy', 'extra bold', 'black'\n",
    "    weight=None, \n",
    "    \n",
    "    # str, default: 'normal'\n",
    "    # 'ultra-condensed', 'extra-condensed', 'condensed', 'semi-condensed', 'normal', 'semi-expanded', 'expanded', 'extra-expanded' or 'ultra-expanded'\n",
    "    stretch=None, \n",
    "    \n",
    "    # str or float, 字号, default: 10\n",
    "    # 'xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'\n",
    "    size=None, \n",
    "    fname=None,    # str, 字体文件\n",
    "    math_fontfamily=None)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- family\n",
    "1. sans-serif: <font style=\"font-family:sans-serif;font-size:medium;\">font-family</font>\n",
    "2. serif: <font style=\"font-family:serif;font-size:medium;\">font-family</font>\n",
    "3. cursive: <font style=\"font-family:cursive;font-size:medium;\">font-family</font>\n",
    "4. fantasy: <font style=\"font-family:fantasy;font-size:medium;\">font-family</font>\n",
    "5. monospace: <font style=\"font-family:monospace;font-size:medium;\">font-family</font>\n",
    "\n",
    "- style\n",
    "1. normal: <font style=\"font-style:normal;font-size:medium;\">style</font>\n",
    "2. italic: <font style=\"font-style:italic;font-size:medium;\">style</font>\n",
    "3. oblique: <font style=\"font-style:oblique;font-size:medium;\">style</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install --upgrade matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T08:56:42.249074Z",
     "iopub.status.busy": "2021-11-25T08:56:42.248116Z",
     "iopub.status.idle": "2021-11-25T08:56:42.418993Z",
     "shell.execute_reply": "2021-11-25T08:56:42.418297Z",
     "shell.execute_reply.started": "2021-11-25T08:56:42.249040Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import sys\n",
    "sys.path.append(\"external-libraries\")\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotlib.font_manager as font_manager\n",
    "\n",
    "x = np.arange(0, 10, 0.2)\n",
    "y = np.sin(x)\n",
    "\n",
    "font_MSYH = font_manager.FontProperties(fname=\"data/data118028/MSYH.TTC\", size=24, stretch=0)\n",
    "font_SIMSUN = font_manager.FontProperties(fname=\"data/data118028/SIMSUN.TTC\", size='x-large', weight='bold')\n",
    "font_TIMES = font_manager.FontProperties(fname=\"data/data118028/TIMES.TTF\", size='xx-large', weight='bold')\n",
    "font_TIMES.set_stretch(\"ultra-condensed\")\n",
    "\n",
    "fig = plt.figure(constrained_layout=True)\n",
    "\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_title('Axes\\'s Title', color=\"deepskyblue\", fontproperties = font_MSYH)\n",
    "ax.set_xlabel('xaxis label', fontproperties=font_SIMSUN)\n",
    "ax.set_ylabel('yaxis label', fontproperties=font_TIMES)\n",
    "ax.plot(x,y)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.title 和 set_title\n",
    "\n",
    "1. [pyplot API](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.title.html#matplotlib.pyplot.title)\n",
    "```python\n",
    "pyplot.title(\n",
    "    label,         # str, 标题文本内容\n",
    "    fontdict=None, # dict, 文本样式配置字典\n",
    "    loc=None,      # str, 标题文本位置, default:'center',  {'center', 'left', 'right'}\n",
    "    pad=None,      # float, 标题与Axes顶部的偏移量, default:6.0\n",
    "    y=None,        # float, 标题的垂直轴位置（1.0 是顶部）, default:None表示自动确定\n",
    "    **kwargs)      # Text properties\n",
    "```\n",
    "\n",
    "2. [OO API](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.set_title.html#matplotlib.axes.Axes.set_title)\n",
    "\n",
    "```python\n",
    "Axes.set_title(\n",
    "    label, fontdict=None, loc=None, pad=None, *, y=None, **kwargs)\n",
    "# 参数与 `matplotlib.pyplot.title`一模一样\n",
    "```\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-24T13:38:30.080134Z",
     "iopub.status.busy": "2021-11-24T13:38:30.079632Z",
     "iopub.status.idle": "2021-11-24T13:38:31.298842Z",
     "shell.execute_reply": "2021-11-24T13:38:31.297994Z",
     "shell.execute_reply.started": "2021-11-24T13:38:30.080084Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotlib.font_manager as font_manager\n",
    "\n",
    "x1 = np.linspace(-np.pi, np.pi, 170)\n",
    "y1 = (1 + np.sin(100 * np.pi * x1)) * np.sinc(x1)\n",
    "fig, axs = plt.subplots(2, 3, figsize=(9, 6), layout=\"tight\")\n",
    "locs = ['center', 'left', 'right']\n",
    "colors = np.arange(0.3, 1.2, 0.3)\n",
    "for ax, loc in zip(axs[0, :], locs):\n",
    "    ax.plot(x1, y1)\n",
    "    ax.set_title('Title', loc=loc)\n",
    "for ax, color in zip(axs[1, :], colors):\n",
    "    ax.plot(x1, y1)\n",
    "    ax.set_title('Title', fontdict=dict(color=plt.cm.rainbow(color), size=20))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.figtext\n",
    "\n",
    "- [pyplot API](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.figtext.html#matplotlib.pyplot.figtext)\n",
    "\n",
    "```python\n",
    "pyplot.figtext(\n",
    "    x, y,          # float, figure的文本左下角的位置, 取值在[0 1], 是归一化的位置\n",
    "    s,             # str, figure的文本内容\n",
    "    fontdict=None, # dic, figure的文本配置字典\n",
    "    **kwargs)      # Text properties\n",
    "```\n",
    "\n",
    "- [OO API](https://matplotlib.org/stable/api/figure_api.html#matplotlib.figure.Figure.text)\n",
    "\n",
    "```python\n",
    "Figure.text(x, y, s, fontdict=None, **kwargs)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-24T13:53:23.200332Z",
     "iopub.status.busy": "2021-11-24T13:53:23.199621Z",
     "iopub.status.idle": "2021-11-24T13:53:23.325235Z",
     "shell.execute_reply": "2021-11-24T13:53:23.324427Z",
     "shell.execute_reply.started": "2021-11-24T13:53:23.200292Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x1 = np.linspace(-np.pi, np.pi, 170)\n",
    "y1 = (1 + np.sin(100 * np.pi * x1)) * np.sinc(x1)\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "fig.text(0.7, 0.7, s=\"figtext\", color=\"orange\", fontsize=16)\n",
    "ax.plot(x1, y1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.suptitle\n",
    "\n",
    "- [pyplot API](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.suptitle.html)\n",
    "\n",
    "```python\n",
    "pyplot.suptitle(\n",
    "    t,     # figure的 suptitle文本内容\n",
    "    x, y,  # 位置, default: x=0.5, y=0.98\n",
    "    horizontalalignment, verticalalignment, # 文本对齐方式 default: center, top\n",
    "    fontsize, fontweight,  # 字体样式设置, default: 'large', 'normal'\n",
    "    **kwargs) -> text.Text\n",
    "```\n",
    "\n",
    "- [OO API](https://matplotlib.org/stable/api/figure_api.html#matplotlib.figure.Figure.suptitle)\n",
    "\n",
    "```python\n",
    "Figure.suptitle(\n",
    "    t, x, y, \n",
    "    horizontalalignment, verticalalignment, \n",
    "    fontsize, fontweight, **kwargs) -> text.Text\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-24T14:18:24.943972Z",
     "iopub.status.busy": "2021-11-24T14:18:24.943030Z",
     "iopub.status.idle": "2021-11-24T14:18:25.063862Z",
     "shell.execute_reply": "2021-11-24T14:18:25.063106Z",
     "shell.execute_reply.started": "2021-11-24T14:18:24.943935Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x1 = np.linspace(-np.pi, np.pi, 170)\n",
    "y1 = (1 + np.sin(100 * np.pi * x1)) * np.sinc(x1)\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "# 设置文本 水平右对齐，垂直底部对齐\n",
    "fig.suptitle(\"suptitle\", horizontalalignment=\"right\", verticalalignment=\"bottom\", bbox=dict(facecolor='lightsteelblue', edgecolor=\"steelblue\", alpha=0.5))\n",
    "ax.plot(x1, y1)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.xlabel和ylabel\n",
    "\n",
    "- pyplot API: [pyplot.xlabel](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xlabel.html#matplotlib.pyplot.xlabel) 和 [pyplot.ylabel](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xlabel.html#matplotlib.pyplot.ylabel)\n",
    "\n",
    "```python\n",
    "pyplot.xlabel(\n",
    "    xlabel,        # str, x轴标签文本内容\n",
    "    fontdict=None, # dict\n",
    "    labelpad=None, # float, 文本的bounding box与 x轴之间的间距, default: 4.0\n",
    "    loc=None,      # str, 文本位置, {'left', 'center', 'right'}, default: 'center'\n",
    "    **kwargs)      # Text properties\n",
    "```\n",
    "\n",
    "- OO API: [Axes.set_xlabel](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.set_xlabel.html#matplotlib.axes.Axes.set_xlabel) 和 [Axes.set_ylabel](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.set_xlabel.html#matplotlib.axes.Axes.set_ylabel)\n",
    "\n",
    "```python\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T09:20:51.945466Z",
     "iopub.status.busy": "2021-11-25T09:20:51.944522Z",
     "iopub.status.idle": "2021-11-25T09:20:52.077206Z",
     "shell.execute_reply": "2021-11-25T09:20:52.076604Z",
     "shell.execute_reply.started": "2021-11-25T09:20:51.945431Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import sys \n",
    "sys.path.append('/home/aistudio/external-libraries')\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "reg = np.random.RandomState(1024)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(range(10), reg.randn(10))\n",
    "ax.set_xlabel(\"x label\", labelpad=0.7, loc=\"left\", fontsize=20, fontstyle=\"italic\")\n",
    "ax.set_ylabel(\"y label\", backgroundcolor=plt.cm.Oranges(0.1), color=plt.cm.Oranges(0.9), rotation=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.字体的属性设置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T09:29:50.868491Z",
     "iopub.status.busy": "2021-11-25T09:29:50.867505Z",
     "iopub.status.idle": "2021-11-25T09:29:50.887069Z",
     "shell.execute_reply": "2021-11-25T09:29:50.886378Z",
     "shell.execute_reply.started": "2021-11-25T09:29:50.868454Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "STIXSizeTwoSym\t\t|\tDejaVu Serif\t\t|\tcmr10\t\t\t|\tSTIXNonUnicode\t\t|\t\n",
      "DejaVu Sans Mono\t|\tcmss10\t\t\t|\tSTIXSizeFourSym\t\t|\tDejaVu Serif\t\t|\tcmtt10\t\t\t|\t\n",
      "STIXSizeOneSym\t\t|\tSTIXSizeFourSym\t\t|\tSTIXNonUnicode\t\t|\tDejaVu Serif Display\t|\tSTIXSizeOneSym\t\t|\t\n",
      "cmmi10\t\t\t|\tDejaVu Serif\t\t|\tSTIXGeneral\t\t|\tDejaVu Sans Mono\t|\tSTIXGeneral\t\t|\t\n",
      "DejaVu Sans\t\t|\tDejaVu Sans\t\t|\tDejaVu Sans\t\t|\tDejaVu Sans Mono\t|\tcmsy10\t\t\t|\t\n",
      "DejaVu Sans Display\t|\tSTIXSizeTwoSym\t\t|\tDejaVu Sans Mono\t|\tcmex10\t\t\t|\tSTIXNonUnicode\t\t|\t\n",
      "STIXSizeFiveSym\t\t|\tSTIXGeneral\t\t|\tSTIXNonUnicode\t\t|\tDejaVu Sans\t\t|\tDejaVu Serif\t\t|\t\n",
      "STIXGeneral\t\t|\tSTIXSizeThreeSym\t|\tcmb10\t\t\t|\tSTIXSizeThreeSym\t|\tDejaVu Serif\t\t|\t\n",
      "Lato\t\t\t|\tLato\t\t\t|\tDejaVu Sans\t\t|\tDejaVu Sans Mono\t|\tLato\t\t\t|\t\n",
      "Noto Mono\t\t|\tLato\t\t\t|\tLiberation Serif\t|\tDejaVu Sans\t\t|\tLiberation Mono\t\t|\t\n",
      "Liberation Serif\t|\tLato\t\t\t|\tDejaVu Sans\t\t|\tFZSongYi-Z13S\t\t|\tWenQuanYi Zen Hei\t|\t\n",
      "Lato\t\t\t|\tDejaVu Sans\t\t|\tLato\t\t\t|\tDejaVu Sans Mono\t|\tLiberation Serif\t|\t\n",
      "Liberation Mono\t\t|\tLato\t\t\t|\tDejaVu Serif\t\t|\tLiberation Mono\t\t|\tLato\t\t\t|\t\n",
      "Liberation Sans\t\t|\tDejaVu Serif\t\t|\tLato\t\t\t|\tLiberation Serif\t|\tLiberation Sans Narrow\t|\t\n",
      "AR PL UKai CN\t\t|\tLiberation Sans Narrow\t|\tLato\t\t\t|\tLiberation Sans\t\t|\tDejaVu Sans\t\t|\t\n",
      "DejaVu Serif\t\t|\tWenQuanYi Micro Hei\t|\tLiberation Sans Narrow\t|\tLiberation Sans\t\t|\tDejaVu Sans\t\t|\t\n",
      "Droid Sans Fallback\t|\tDejaVu Sans Mono\t|\tDejaVu Serif\t\t|\tLato\t\t\t|\tLiberation Sans Narrow\t|\t\n",
      "DejaVu Serif\t\t|\tLato\t\t\t|\tDejaVu Sans Mono\t|\tLato\t\t\t|\tLiberation Sans\t\t|\t\n",
      "DejaVu Sans\t\t|\tDejaVu Serif\t\t|\tAR PL UMing CN\t\t|\tLato\t\t\t|\tLato\t\t\t|\t\n",
      "Lato\t\t\t|\tLato\t\t\t|\tFZHuaLi-M14S\t\t|\tDejaVu Sans\t\t|\tDejaVu Sans\t\t|\t\n",
      "DejaVu Serif\t\t|\tLiberation Mono\t\t|\t"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import sys \n",
    "sys.path.append('/home/aistudio/external-libraries')\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.font_manager as font_manager\n",
    "import numpy as np\n",
    "\n",
    "for idx, font in enumerate(font_manager.fontManager.ttflist, 1):\n",
    "    if idx % 5 == 0: print()\n",
    "    if len(font.name) > 15: print(\"{}\".format(font.name), end=\"\\t|\\t\")\n",
    "    elif len(font.name) < 9: print(\"{}\".format(font.name), end=\"\\t\\t\\t|\\t\")\n",
    "    else: print(\"{}\".format(font.name), end=\"\\t\\t|\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 修改字体默认属性，完成全局字体的更改\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimSun']    # 指定默认字体为新宋体\n",
    "plt.rcParams['axes.unicode_minus'] = False      # 解决保存图像时 负号'-' 显示为方块和报错的问题"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 局部字体的修改方法1\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.font_manager as font_manager\n",
    "\n",
    "x = range(11)\n",
    "plt.plot(x, label='小示例图标签')\n",
    "\n",
    "# 直接用字体的名字\n",
    "plt.xlabel('x 轴名称参数', fontproperties='Microsoft YaHei', fontsize=16)          # 设置 x轴名称，采用 Microsoft YaHei\n",
    "plt.ylabel('y 轴名称参数', fontproperties='Microsoft YaHei', fontsize=14)          # 设置 Y轴名称\n",
    "plt.title('坐标系的标题',  fontproperties='Microsoft YaHei', fontsize=20)          # 设置 坐标系标题的字体\n",
    "plt.legend(loc='lower right', prop={\"family\": 'Microsoft YaHei'}, fontsize=10)    # 设置 小示例图的字体"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T09:42:45.136809Z",
     "iopub.status.busy": "2021-11-25T09:42:45.136202Z",
     "iopub.status.idle": "2021-11-25T09:42:45.277193Z",
     "shell.execute_reply": "2021-11-25T09:42:45.276668Z",
     "shell.execute_reply.started": "2021-11-25T09:42:45.136775Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 局部字体的修改方法2\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.font_manager as font_manager\n",
    "\n",
    "x = range(11)\n",
    "reg = np.random.RandomState(1024)\n",
    "plt.plot(x, reg.randn(11), label='小示例图标签')\n",
    "font1_props = font_manager.FontProperties(fname=r'data/data118028/MSYH.TTC')\n",
    "font2_props = font_manager.FontProperties(fname=r'data/data118028/SIMSUN.TTC')\n",
    "\n",
    "# 将x轴标签字体设置为font1_props，字号设置为16\n",
    "plt.xlabel('x 轴名称参数', fontproperties=font1_props, fontsize=16)\n",
    "# 将y轴标签字体设置为font2_props，字号设置为14\n",
    "plt.ylabel('y 轴名称参数', fontproperties=font2_props, fontsize=14)\n",
    "# 将标题字体设置为font2_props，字号设置为20\n",
    "plt.title('坐标系的标题',  fontproperties=font2_props, fontsize=20)\n",
    "# 将图例字体设置为font1_props，字号设置为10\n",
    "plt.legend(loc='upper right', prop=font1_props, fontsize=10)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7.数学表达式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2021-11-25T10:02:58.124059Z",
     "iopub.status.busy": "2021-11-25T10:02:58.123652Z",
     "iopub.status.idle": "2021-11-25T10:02:58.341201Z",
     "shell.execute_reply": "2021-11-25T10:02:58.340624Z",
     "shell.execute_reply.started": "2021-11-25T10:02:58.124029Z"
    },
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import sys\n",
    "sys.path.append('/home/aistudio/external-libraries')\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.rcdefaults()\n",
    "t = np.arange(0.0, np.pi, 0.01)\n",
    "s = 2.0*(1+np.cos(80*np.pi*t))*np.sin(2*np.pi*t)\n",
    "\n",
    "fig = plt.figure(dpi=90)\n",
    "ax = fig.add_subplot(111)\n",
    "\n",
    "ax.plot(t, s)\n",
    "ax.set_title(r'$\\alpha_i > \\beta_i$', fontsize=20)\n",
    "ax.text(1, -2.0, r'$\\sum_{i=0}^\\infty x_i$', fontsize=20)\n",
    "content = r'$\\mathcal{A}(1+\\mathrm{cos}(40\\omega t))\\mathrm{sin}(2 \\omega t)$'\n",
    "ax.text(0.6, 3.0, content, fontsize=20)\n",
    "ax.set_xlabel('time (s)')\n",
    "ax.set_ylabel('volts (mV)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T10:25:28.865297Z",
     "iopub.status.busy": "2021-11-25T10:25:28.864284Z",
     "iopub.status.idle": "2021-11-25T10:25:29.023933Z",
     "shell.execute_reply": "2021-11-25T10:25:29.023227Z",
     "shell.execute_reply.started": "2021-11-25T10:25:28.865259Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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iEjMzm+PuaQVZR9cUSpF27doxevToQgVCnz59MDPMjKSkJCpWrEj9+vW55JJLGD58OBkZGcVQsYiUNAqFE1Bqamr0BZ7bT+PGjSnsWaC7s3fvXr799lumTZtG//796dKlC9u3by/aDyIiJY5C4QTUv39/AN5//33S09MP+/n4449JSkrilltuKXQT0vTp09m3bx9z5syhW7duAHz66af07du3yD6DiJRMCoUT0E033USFChWYOXMmqamph/3MmjWLpKSk474onJKSwjnnnMOkSZNo3LgxAK+//jrz5s0rio+Qo61bt9KvXz9q165NhQoVuOCCC1i5cmWx7U9EjqZQOAHVqVOHnj17MnLkyKPmjRw5kssvv5xTTz21SPaVkpLCbbfdFk2/8847OS7n7mRmZh7zJzdbtmzh/PPPZ/Xq1YwcOZJhw4axdOlSnZ2IJJhuST1B3XrrrXTu3JmPP/6YCy+8EIDPP/+cxYsX8/jjjxfpvlq0aBG9XrNmTY7LjB49Ol9f4Lld5xg0aBDVqlXjnXfeITk5GYB169bx3//93+zcuZMqVaoUonIRKSiFwgmqU6dOtGjRghEjRkShMGLECBo2bEjXrl1zXGf48OH079+f9PR0UlNT872v/FywvuKKK5g1a1a+t5ndtm3beOGFF5g4cWIUCABNmzbF3dm9e7dCQSRBFAonsP79+zNkyBCeeuopypUrx7hx47j77rtJSsq5VbB69eo0bdqUlJSUAu1n2bJl0euGDRvmuEytWrWoXr16gbabZdq0abg7F1988WHvr1+/nipVqlCnTp1CbVdECk7XFE5gffr0ITMzk3HjxvHqq6+ya9euPC8w//znP+frr7+mSZMm+d5HRkYGzz33XDSd21nI6NGjKV++/DF/cjJ79mxq1KhBxYoVD3t/ypQpdOvWLdeQE5GiF8uZgpnVAIYDrQEHbnb3z+Ko5URWp04devXqxciRI6lQoQI9evSgXr16RbLt/fv3s3jxYu69997oDqCePXvSpk2bHJc/nuaj+fPns337drZv306NGjUA+Pe//827777L22+/XahtikjhxNV89DdgirtfbWYpQKWY6jjhDRgwgC5dugAwefLkItlmTn0qdejQIce7nbLUrl2b2rVrF2p/CxYs4JRTTuH666/nzjvvZNmyZTzwwAP069ePSy+9tFDbFJHCSXgomFl1oCPQB8DdMwD1oVBInTt3ZuDAgWRkZNC9e/ci226FChWoU6cOLVu2pHfv3txwww25Nv8cj/Xr17Nx40YmTZrE6NGj6dWrFzVq1OCuu+7i/vvvL/L9iUjeEt4hnpm1AYYBS4GzgTnAXe6ea2f96hCv9Hr77bfp0aMHW7dupWbNmnGXI1KqnCgd4pUDzgGedfe2wC7gniMXMrMBZjbbzGZv3rw50TVKgsyfP5+GDRsqEERKiDhCYS2w1t1nhtPjCULiMO4+zN3T3D2tbt26CS1QEmfBggW5XrwWkcRL+DUFd99gZt+Y2Rnu/iVwEUFTkpRB48aNi7sEEckmrruPfgW8GN55tAJQBzciIiVALKHg7vOBAl38EBGR4qdHRUVEJKJQEBGRiEJBREQiuV5TMLOjbhPNzt3nFn05IiISp7wuND+RxzwHuhRxLSIiErNcQ8Hdj+4VTURESrVjXlMws0pmdp+ZDQunm5vZ5cVfmoiIJFp+LjQ/T9CL6fnh9LfAw8VWkYiIxCY/odDU3R8H9gO4+27AirUqERGJRX5CIcPMKhJcXMbMmgL7irUqERGJRX66uRgCTAFON7MXgQsIB8gREZHS5Zih4O5TzWwu0J6g2egud99S7JWJiEjC5bdDvJ8CHQiakMoDE4utIhERiU1+bkl9BrgNWAQsBm41s78Xd2EiIpJ4+TlT6AK09HAwZzMbDSwp1qpERCQW+bn76GugQbbp08P3RESklMmrQ7zJBNcQqgLpZvZ5OP1j4PPElCciIomUV/PR0IRVISIiJUJeHeJ9mMhCREQkfvm5+6i9mc0ys51mlmFmB8xsRyKKExGRxMrPheangd7AMqAicAugW1JFREqhfA3H6e5fA8nufsDdnwe6FW9ZIiISh/w8p7DbzFKA+Wb2OLAeje0sIlIq5efL/QYgGbgT2EXwnMLPirMoERGJR346xFsdvtwDPFS85YiISJzyenhtEeEYCjlx9/8olopERCQ2eZ0pZI3DfBXwMbC1+MsREZE45fXw2moAM/sR8CowFxgJvJPVOZ6IiJQux7zQ7O73Ac2BEQQjri0zs0fCYTlFRKQUye9zCg5sCH8ygZrA+PAWVRERKSWOefeRmd0F3AhsAYYDv3f3/WaWRPCU86DiLVFERBIlPw+v1QJ6Zbs1FQB3P2hml+eyjoiInIDy85zCkDzmpRdtOSIiEqfYuqsws2Qzm2dmb8RVg4iIHC7OPozuAnSmISJSgsQSCmZWH7iM4MK1iIiUEHGdKfyV4K6lg7ktYGYDzGy2mc3evHlzwgoTESnLEh4K4R1Lm9x9Tl7Lufswd09z97S6desmqDoRkbItjjOFC4ArzWwVMA7oYmZjYqhDRESOkPBQcPfB7l7f3RsB1wHvu/v1ia5DRESOphHUREQkkp8nmouNu38AfBBnDSIicojOFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJKJQEBGRiEJBREQiCgUREYkoFEREJFIu7gLkxLN3+14WvbSIdre3K/C6G+Zv4Id1P9C8R3MAFr64kE8f+xQcUqqmcNmzl3HK2acUdckikk86U5AC27t9L7OemVWodTfM38Cyt5ZF0zUb16TPh30YuGggHe/vyBsD3iiqMkWkEHSmIAU27Z5pbFu+jefaPEeTS5pQ+UeVWfrKUjL3ZZLaM5XOD3UmfWI6s56exQ3TbmDnhp2M+ukobpx2I9MfmE7mnkzWfLKGDoM70Pra1tF267evz461O2L8ZCKiUJACu/jRi9m0eBO3zb+N5e8uZ+n4pdzy+S3gMPbKsaz+aDUte7YkfUI6s/4+i6+nfE2nhzpRvUF1Ov+xM+tmr6PH0z2O2u68EfNo1r1Z4j+QiEQSHgpmdjrwAnAy4MAwd/9bouuQorH83eUsf3c5/2j7DwAydmbw3bLvaNixId3/tzvPtn6W+u3rc1bvs/LczsrpK5k3Yh59P+mbiLJFJBdxnClkAr9z97lmVhWYY2ZT3X1pDLXIcXJ3OgzuQNqtaUfN27F2B5Zk7Ny4Ez/oWJLluI2NCzcy+ZbJ/PLtX1KpdqXiLllE8pDwC83uvt7d54avfwDSgXqJrkMKL6VqChk/ZADQrGsz5o+cT8bOYHrHtzvYtWkXBzMP8q+b/8XPxv6MOi3r8NmTnx21LsD3a77n5V4v0/P/elK7Re3EfxgROYy5e3w7N2sEfAS0dvcdR8wbAAwAaNCgwbmrV69OfIGSqwm/mMDGhRtp1r0Z1epXY97weQCkVEmh55ieLHpxEXu376Xrk13Z98M+/tnun1w78VqqnFyFMV3HcGD/AToM7sCKqStIn5BO9YbVAUgql8SA2QPi/GgipYaZzXH3o0/j81onrlAwsyrAh8D/uPtreS2blpbms2fPTkxhIiKlRGFCIZbnFMysPDABePFYgSAiIomT8FAwMwNGAOnu/mSi9y8iIrmL40zhAuAGoIuZzQ9/jr5pXUREEi7ht6S6+ydAzvcmiohIrNT3kYiIRBQKIiISUSiIiEhEoSAiIhGFgoiIRBQKIiISUSiIiEhEoSAiIhGFgoiIRBQKIiISUSiIiEhEoSAiIhGFgoiIRBQKIiISUSiIiEhEoSAiIhGFgoiIRBQKIiISUSiIiEhEoSAiZdorS15h1PxRxbLtxz99nA9WfXDU+7e9cRupT6dS5ZEq1HysJh2f78i0FdOKpYaCUiiISJkWRyjsydzDnefdycRrJzKm5xjqVKpD9xe7M2PtjGKpoyDKxV2AiEhZM/o/Rx823a1ZNxr/rTEvLXqJ9vXbx1RVQGcKIlJm9Xm9DxPSJ/Dh6g+xhwx7yHjwgwcBmPTFJNKGpXHSwydxytBTGDR1EPsP7Adg5baVVP1TVR6Y/kC0rf0H9nPusHPp+HxHDvpBGv21Ed/t+Y6HPnwo2nZOZw0AyUnJ1DipBhkHMor7Ix+TzhREpMy6v+P9rPl+Ddv3bueZy54BoH61+ryy5BV6T+jNrefeyiMXPcLyrcsZ/N5gDvpBhl46lMY1GzP0kqHc+fadXHnGlaSdlsbDHz3Ml1u+ZOHAhSRZEhOvnUjn0Z25utXV3HLOLQC0qtsq2re7c8AP8P3e73lhwQss27qM4VcOj+U4ZKdQEJEyq2mtptSqWIuDfjBqtnF3fj/199x49o1RUNAUKpSrwB1v3cHgDoOpXak2t6bdysQvJnLT6zfxzyv+ySOfPMJT3Z6iSc0mALQ9tS3lkspRv1r9HJuEXl7yMr0n9AagcvnKvHz1y5xX77zEfPA8qPlIRCSbr777ijXfr+GaVteQeTAz+unSuAt7M/eyeNPiaNkRV45g3Q/r6DK6C50bdWZgu4H53k/Xpl2Z1X8Wb//ybXq27Ml146/LtXkpkXSmICKSzZbdWwDo8VKPHOd/s+Ob6HW9avW4sMGFTP5qMgPT8h8IADUr1iStYhoQXGhe98M6Hpj+AB/1/aiQlRcNhYKISDa1KtYCYNjlw2h7atuj5jeu0Th6PTF9Im989QZnn3w2g6YNomuzrlQqX6lQ+217SlvGLR5XuKKLkJqPRKRMS0lOYW/m3mj6jDpnUK9qPVZtX0XaaWlH/dSuVBsIzihue/M2bm93O1Oun8LWPVv5w9Q/5Lnt3Lg7n639jMY1Gx9z2eKmMwURKdNS66Qy6ctJvP7F69SvVp/Tqp7GE5c+wQ0Tb2DHvh10b96dlOQUVmxbwetfvM74a8ZTqXwlBr45kKopVXns4seonFKZv/f4O7+Y8At6texF58ado22/uexNujXrRpWUKpxR+wzmb5jPkzOepGdqTxpUb8B3u79j9ILRzFg7g8m9J8d8NBQKIlLG3d7uduZtmMfNk25m295tDPnpEB7s9CDVKlTjkU8eYeT8kSRbMk1qNuHyFpeTkpzC2EVjeS39NT7s8yGVUyoDcF3r65iQPoG+k/qyaOAiqlaoyp8v+TN3vHUHl710Gbv372b6TdNpVKMRyZbMve/dy+bdm6lbqS5tTmnDJ30/4Sen/yTmowHm7nHXcExpaWk+e/bsuMsQETmhmNkcd08ryDqxXFMws25m9qWZfW1m98RRg4iIHC3hoWBmycDfge5AK6C3mbXKey0REUmEOM4UzgO+dvcV7p4BjAOuiqEOERE5QhyhUA/4Jtv02vA9ERGJWYm9+8jMBgADwsl9ZrY4r+XLkDrAlriLKCF0LA7RsThEx+KQMwq6Qhyh8C1werbp+uF7h3H3YcAwADObXdAr6KWVjsUhOhaH6FgcomNxiJkV+LbNOJqPZgHNzayxmaUA1wH/iqEOERE5QsLPFNw908zuBN4BkoGR7r4k0XWIiMjRYrmm4O5vAW8VYJVhxVXLCUjH4hAdi0N0LA7RsTikwMfihHiiWUREEkO9pIqISKREh4K6wwiY2elmNt3MlprZEjO7K+6a4mZmyWY2z8zeiLuWOJlZDTMbb2ZfmFm6mcXfo1pMzOw34b+PxWY21sxOirumRDGzkWa2Kfut+2ZWy8ymmtmy8HfN/GyrxIaCusM4TCbwO3dvBbQH7ijDxyLLXUB63EWUAH8Dprh7KnA2ZfSYmFk94NdAmru3JriJ5bp4q0qoUUC3I967B3jP3ZsD74XTx1RiQwF1hxFx9/XuPjd8/QPBP/wy+xS4mdUHLgOGx11LnMysOtARGAHg7hnuvj3WouJVDqhoZuWASsC6mOtJGHf/CNh6xNtXAaPD16OB/8zPtkpyKKg7jByYWSOgLTAz5lLi9FdgEHAw5jri1hjYDDwfNqUNN7PKcRcVB3f/FhgKrAHWA9+7+7vxVhW7k919ffh6A3ByflYqyaEgRzCzKsAE4L/cfUfc9cTBzC4HNrn7nLhrKQHKAecAz7p7W2AX+WwiKG3C9vKrCILyNKCymV0fb1Ulhwe3mebrVtOSHAr56g6jrDCz8gSB8KK7vxZ3PTG6ALjSzFYRNCl2MbMx8ZYUm7XAWnfPOmscTxASZdHFwEp33+zu+4HXgPNjriluG83sVIDw96b8rFSSQ0HdYYTMzAjajdPd/cm464mTuw929/ru3ojg/4n33b1M/kXo7huAb8wsq9Ozi4ClMZYUpzVAezOrFP57uYgyetE9m38BN4WvbwIm5WelEttLqrrDOMwFwA3AIjObH753b/hkuJRtvwJeDP9wWgH0jbmeWLj7TDMbD8wluFtvHmXoyWYzGwt0AuqY2VpgCPAo8IqZ9QNWA9fka1t6ollERLKU5OYjERFJMIWCiIhEFAoiIhJRKIiISEShICIiEYWCSA7MrFH2HidzWaZTQXtpNbMPzEzjB0uJpVAQEZGIQkHKPDNrZ2YLzewkM6tsZkuAKtnmNzKzj81sbviTvfuEamb2Zjjux3NmlhSuc6mZfRYu/2rYb5VIiVdin2gWSRR3n2Vm/wIeBioCY4Cd2RbZBFzi7nvNrDkwFshqAjqPYLyP1cAUoJeZfQDcB1zs7rvM7A/Ab4E/JuLziBwPhYJI4I8E/W3tJRisJXtnjOWBp82sDXAAaJFt3ufuvgKirgY6hNtoBXwadMNDCvBZMdcvUiQUCiKB2gRNRuWBI4dx/A2wkWBksySCL/0sR/YT44ABU929d/GUKlJ8dE1BJPAP4H7gReCxI+ZVB9a7+0GCjgmTs807L+zJNwm4FvgEmAFcYGbNAMLrFC0QOQHoTEHKPDO7Edjv7i+FY4P/G+iSbZFngAnhclMIBrPJMgt4GmgGTAcmuvtBM+sDjDWzCuFy9wFfFe8nETl+6iVVREQiaj4SEZGIQkFERCIKBRERiSgUREQkolAQEZGIQkFERCIKBRERiSgUREQk8v8Ba3ewVA2G9qEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "fig.subplots_adjust(top=0.85)\n",
    "\n",
    "fig.suptitle('figure suptitle', fontsize=14, fontweight='bold')\n",
    "ax.set_title('axes title')\n",
    "ax.set_xlabel('xlabel')\n",
    "ax.set_ylabel('ylabel')\n",
    "# 设置xaxis和yaxis的范围都是[0, 10]\n",
    "ax.axis([0, 10, 0, 10])\n",
    "\n",
    "ax.text(3, 8, 'text1', style='italic',\n",
    "        bbox=dict(facecolor=plt.cm.Oranges(0.1), edgecolor=plt.cm.Oranges(0.9), alpha=0.5, pad=10))\n",
    "\n",
    "ax.text(2, 6, r'$\\vec{\\nabla} \\cdot \\vec{\\mathbf{D}} =\\rho$', fontsize=15)\n",
    "font1 = {\n",
    "    'family': mpl.font_manager.FontProperties(fname=\"data/data118028/TIMES.TTF\").get_family(),\n",
    "    'color':  'purple',\n",
    "    'weight': 'normal',\n",
    "    'size': 10,\n",
    "}\n",
    "ax.text(3, 2, 'text2', fontdict=font1)\n",
    "ax.text(0.95, 0.01, 'text3',\n",
    "        verticalalignment='bottom', horizontalalignment='right',\n",
    "        transform=ax.transAxes,\n",
    "        color='green', fontsize=15)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 二、Tick上的文本\n",
    "\n",
    "- tick（刻度）\n",
    "- ticklabel（刻度标签）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 简单模式\n",
    "\n",
    "- `axis`的 [set_ticks()]() 设置**标签位置**\n",
    "- `axis`的`set_ticklabels()`方设置**标签格式**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T11:17:53.127633Z",
     "iopub.status.busy": "2021-11-25T11:17:53.126844Z",
     "iopub.status.idle": "2021-11-25T11:17:53.272658Z",
     "shell.execute_reply": "2021-11-25T11:17:53.272103Z",
     "shell.execute_reply.started": "2021-11-25T11:17:53.127599Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import sys\n",
    "sys.path.append('/home/aistudio/external-libraries')\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.rcdefaults()\n",
    "t = np.arange(-np.pi/2, np.pi/2+0.001,  0.001)\n",
    "s = np.sinc(np.pi*t)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(t, s)\n",
    "ax.set_xticks(np.arange(-2.0, 2.0+0.5, 0.5))\n",
    "ax.set_xticklabels([\"{:.1f}\".format(i) for i in np.arange(-2.0, 2.0+0.5, 0.5)])\n",
    "ax.spines[[\"top\", \"right\"]].set_visible(False)\n",
    "ax.spines[[\"bottom\", \"left\"]].set_position(('data', 0.0))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Tick Locators and Formatters\n",
    "\n",
    "还可以使用`Tick Locators` and `Formatters`完成对于刻度位置和刻度标签的设置。\n",
    "<a href=\"https://matplotlib.org/stable/_images/inheritance-dda841dcb224d60006db5f49ee5b49b96964e76a.png\"><img src=\"https://matplotlib.org/stable/_images/inheritance-dda841dcb224d60006db5f49ee5b49b96964e76a.png\" style=\"zoom:0.7;\"></a>\n",
    "- 设置标签的位置:\n",
    "  1. [Axis.set_major_locator(locator)](https://matplotlib.org/stable/api/_as_gen/matplotlib.axis.Axis.get_major_formatter.html#matplotlib.axis.Axis.set_major_locator)\n",
    "  2. [Axis.set_minor_locator(locator)](https://matplotlib.org/stable/api/_as_gen/matplotlib.axis.Axis.set_minor_formatter.html#matplotlib.axis.Axis.set_major_locator)\n",
    "\n",
    "  需要传入 [ticker.Locator](https://matplotlib.org/stable/api/ticker_api.html#matplotlib.ticker.Locator) 的实例对象。\n",
    "\n",
    "- 设置标签的格式\n",
    "  1. [Axis.set_major_formatter()](https://matplotlib.org/stable/api/_as_gen/matplotlib.axis.Axis.get_major_formatter.html#matplotlib.axis.Axis.set_major_formatter)\n",
    "  2. [Axis.set_minor_formatter()](https://matplotlib.org/stable/api/_as_gen/matplotlib.axis.Axis.get_major_formatter.html#matplotlib.axis.Axis.set_minor_formatter)\n",
    "\n",
    "这种方式的好处是**不用显式地列举出刻度值列表**。\n",
    "\n",
    "- 设置刻度值的格式\n",
    "  1. [set_major_formatter()]()\n",
    "  2. [set_minor_formatter()]()\n",
    "  \n",
    "  接收字符串格式 [ticker.StrMethodFormatter](https://matplotlib.org/stable/api/ticker_api.html#matplotlib.ticker.StrMethodFormatter) 或 [ticker.FormatStrFormatter](https://matplotlib.org/stable/api/ticker_api.html#matplotlib.ticker.FormatStrFormatter)，也可以接收函数参数 [ticker.FuncFormatter]()等\n",
    "  <br/><br/><br/>\n",
    "- 更多信息请参考 [Matplotlib Reference](https://matplotlib.org/stable/api/ticker_api.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**a) Tick Formatters**\n",
    "\n",
    "<img src=\"https://ai-studio-static-online.cdn.bcebos.com/a6037ba6a3864e84a28a745569c840111fd0c043b7264eaca0035921c35e859e\" style=\"zoom:0.41;\">\n",
    "\n",
    "\n",
    "- [ticker.StrMethodFormatter(fmt)](https://matplotlib.org/stable/api/ticker_api.html#matplotlib.ticker.StrMethodFormatter)\n",
    "\n",
    "  `fmt`: <a href=\"https://docs.python.org/3/library/stdtypes.html#str.format\">str.format</a>\n",
    "\n",
    "- [ticker.FormatStrFormatter(fmt)](https://matplotlib.org/stable/api/ticker_api.html#matplotlib.ticker.FormatStrFormatter)\n",
    "\n",
    "  `fmt`: `'%'`操作符"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T12:20:00.494018Z",
     "iopub.status.busy": "2021-11-25T12:20:00.493087Z",
     "iopub.status.idle": "2021-11-25T12:20:00.945622Z",
     "shell.execute_reply": "2021-11-25T12:20:00.944968Z",
     "shell.execute_reply.started": "2021-11-25T12:20:00.493986Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 接收字符串格式的例子\n",
    "import matplotlib.ticker as ticker\n",
    "fig, axs = plt.subplots(2, 2, figsize=(8, 5), layout=\"tight\")\n",
    "x1 = np.arange(-np.pi/2, np.pi/2+0.001,  0.001)\n",
    "y1 = np.sinc(np.pi*x1)\n",
    "for n, ax in enumerate(axs.flat):\n",
    "    ax.plot(x1*10., y1)\n",
    "\n",
    "formatter = ticker.FormatStrFormatter('%1.1f')\n",
    "axs[0, 1].xaxis.set_major_formatter(formatter)\n",
    "\n",
    "formatter = ticker.FormatStrFormatter('-%1.1f')\n",
    "axs[1, 0].xaxis.set_major_formatter(formatter)\n",
    "\n",
    "# formatter = ticker.StrMethodFormatter(\"{x:1.1f}\")\n",
    "# axs[1, 1].xaxis.set_major_formatter(formatter)\n",
    "# 也可以直接传入 str.format的格式化字符串\n",
    "axs[1, 1].xaxis.set_major_formatter(\"{x:1.1f}\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T12:28:29.292500Z",
     "iopub.status.busy": "2021-11-25T12:28:29.291849Z",
     "iopub.status.idle": "2021-11-25T12:28:29.428057Z",
     "shell.execute_reply": "2021-11-25T12:28:29.427321Z",
     "shell.execute_reply.started": "2021-11-25T12:28:29.292468Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 接收函数的例子\n",
    "def formatoddticks(x, pos):\n",
    "    \"\"\"Format odd tick positions.\"\"\"\n",
    "    return f'{x:1.1f}' if x % 2 else f'{x}'\n",
    "\n",
    "x1 = np.arange(-np.pi/2, np.pi/2+0.001,  0.001)\n",
    "y1 = np.sinc(np.pi*x1)\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(x1, y1)\n",
    "# ax.xaxis.set_major_formatter(formatoddticks)\n",
    "ax.xaxis.set_major_formatter(lambda x, _: f'{x:1.1f}' if x % 2 else f'{x}')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**b) Tick Locators**\n",
    "\n",
    "在普通的绘图中，我们可以直接通过上图的 `Axes.set_xticks()`/`Axes.set_yticks()` 进行设置刻度的位置，缺点是需要自己指定或者接受matplotlib默认给定的刻度。\n",
    "\n",
    "当需要更改刻度的位置时，matplotlib给了常用的几种 `Locator` 的类型。如果绘制更复杂的图，可以先设置`Locator`，然后通过 `xaxis.set_major_locator(locator)` 绘制。\n",
    "\n",
    "```python\n",
    "# 在合适的位置找到最多带有刻度的间隔数\n",
    "locator=plt.MaxNLocator(nbins=7)\n",
    "# 直接指定刻度所在的位置\n",
    "locator=plt.FixedLocator(locs=[0.0, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.0])\n",
    "# 自动分配刻度值的位置\n",
    "locator = plt.AutoLocator()\n",
    "# 面元间距是1，从0.5开始\n",
    "locator = plt.IndexLocator(offset=0.5, base=1)\n",
    "# 将刻度的标签设置为1.5的倍数\n",
    "locator = plt.MultipleLocator(1.5)\n",
    "# 线性划分5等分，4个刻度\n",
    "locator = plt.LinearLocator(numticks=5)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T12:51:26.050839Z",
     "iopub.status.busy": "2021-11-25T12:51:26.049894Z",
     "iopub.status.idle": "2021-11-25T12:51:26.513239Z",
     "shell.execute_reply": "2021-11-25T12:51:26.512055Z",
     "shell.execute_reply.started": "2021-11-25T12:51:26.050766Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RALqisdJYo9rU3GzYll/BuEGRPbrP+EGRbM+voFlbi3sFOxKcJCCnxde51rHvEZFhwHDg8xaHQ0QkXURWisj57T1ERG6xzksvLi62odjKHbbmlzN6QCT+fp1f4K+1kfHhBAX4sXW/Jjh9nMtjjcYZ37T3QA019U2MG9izBGfcoEiq65t0oHEv4e5BxpcDbxpjmlocG2aMSQOuBP4qIiPbutAY84wxJs0YkxYfH++OsqoeMsawdX9Fj4NOoL8foxMj2KotOKrzuhVrNM74Jmflp6ctOOMGOrrSNdb0DnYkOHnAkBZfD7aOteVyWjUZG2PyrH+zgS85ss9c+bD95bVU1Db2OOgAjBsYyZb9FbpGRd+msUa1aVt+BQF+QkpC97vCAVITw/H3E20t7iXsSHDWAKkiMlxEgnAElu/NUBCRMUAMsKLFsRgRCbY+jwPmAltbX6t80+FaVQ9bcMBRMztQXU9hRV2P76V8lsYa1aat+RWkJIR3a62tlkIC/UmJD9cWnF6ixwmOMaYRuAP4CNgGLDbGbBGRh0XkvBanXg68bo6sgo8F0kVkA/AF8GjLGRHKt23dX4EIjBnQ85lPzlagrfk6w6Gv0lij2rN1fwVjbahIgSPWaAtO79DjaeIAxpilwNJWxx5o9fVDbVz3LTDRjjIo77M1v5zk/v3oF9zzXzNnkrR1fwUnj0ns8f2Ub9JYo1o7UF1PQUWtLS3F4Ghxfmd9HqVVdfQPD7blnsozdCVj5TLb8ittCzoRIYEM6x+mTcdKqSM4l4+wY6xfy/tsy6+05X7KczTBUS5RUevY08WuoAOOmpU2HSulWnLGBNu6qAZqd3hvoQmOcontVu1n7ED7Vh4ePSCCvQdqOFTfdPSTlVJ9wtb8CgZEhhDbL8iW+8X0CyIhIpgdBVW23E95jiY4yiV2FjoSnNED7GvBGZUYgTGO/a2UUgpgR0Elo22YyNDSqMQIMou0i8rXaYKjXCKzsJJ+Qf4Migqx7Z7Ofah2FGjgUUpBU7NhV3EVqT1c/6a1UYkRZBZW6ZYNPk4THOUSOwurSEmMQKT7WzS0ltw/jCB/P3ZqzUopBeQcqKGusdn2TXhHJYZzqKGJ3IOHbL2vci9NcJRLZBZVMcrmWlWAvx8j4vuRWahdVEopR5wBxwrEdhpldXntKNTKlC/TBEfZ7mB1PSVVdbYHHXA0HWsXlVIKvhvr19MtGlpzdnnt1ATHp2mCo2z3Xa3K3mZjcDQd55Udoqqu0fZ7K6V8S1ZRFYOiQogICbT1vhEhgSRFh2qC4+M0wVG2cwYFuwf+wXdJU6YGHqX6vJ2FlaS4oCIFjm6vndod7tM0wVG2yyqqol+QP0nRobbfe/ThBEcDj1J9WVOzIcsFY/2cRiVGsKuoisamZpfcX7meJjjKdjsLK0lJCLd1BpXTkNgwggP8tOlYqT4u96BjBpUrxvqBI8Gpb2pm74Eal9xfuZ4mOMp2mUVVLhl/A+DvJ6QmhuvsBqX6OGf3katizSgrcdLucN+lCY6yVVlNPcWVdS4Zf+M0KiFCu6iU6uOcKw3bPYPKydEKjW7Z4MM0wVG2cs6gsnvhrZZSEyMoqKil/FCDy56hlPJumYVVDIwKIdLmGVROYUEBDIkJ04VFfZgtCY6IzBORHSKSJSL3tvH69SJSLCIZ1sfNLV67TkQyrY/r7CiP8pzDM6hc1C8OMHqANh33VRprlNPOwkqXdU85jUqMYKeuu+WzAnp6AxHxB54CTgNygTUissQYs7XVqYuMMXe0ujYWeBBIAwyw1rr2YE/LpTwjs7CKsCB/BkXZP4PKKTXBEdR2FlaRlhzrsuco76KxRjk5Z1DNHtHfpc9JTQznyx1F1Dc2ExSgHR6+xo7/sZlAljEm2xhTD7wOzO/ktWcAnxhjDliB5hNgng1lUh6SWVRJakI4fn72z6BySooOJTTQX3f77Xs01ijguxlUo1zYUgyOgcaNzYa9pdUufY5yDTsSnCQgp8XXudax1i4SkY0i8qaIDOnitYjILSKSLiLpxcXFNhRbucLOwipSElzbbOxnzaTSgcZ9jstjjcYZ3+B877s61rRsLVa+x11tbu8DycaYSThqTi909QbGmGeMMWnGmLT4+HjbC6h6zjmDytW1KnDMcNAWHNWGHsUajTO+wTnw15Vj/QBGxjtmUmms8U12JDh5wJAWXw+2jh1mjCk1xtRZXz4LTO/stcp3uGpn37aMSoygsKJOZ1L1LRprFABZhVUMiHTdDCqn0CB/hsaGaWuxj7IjwVkDpIrIcBEJAi4HlrQ8QUQGtvjyPGCb9flHwOkiEiMiMcDp1jHlg5xBINXFzcagi3D1URprFOBowXFHRQoc8UxXTvdNPU5wjDGNwB04gsU2YLExZouIPCwi51mn/UREtojIBuAnwPXWtQeA3+IIXGuAh61jygftLKwkzEV7ULXmTKKcrUaq99NYowCanXtQuXiKuFNqYji7S6pp0D2pfE6Pp4kDGGOWAktbHXugxef3Afe1c+0CYIEd5VCelVVURYqLZ1A5OWdSac2qb9FYo3IPHqK2odmlq6W35JxJtaek2uXr7ih76cR+ZZvMokqXLZvems6kUqpvynTTAGMnbS32XZrgKFuUH2qgsKLObc3GoDOplOqLnImGq6eIOzlnUmlrse/RBEfZIss5g8pNLTigM6mU6osyC6tIjAwmKtS1M6icdCaV79IER9kiy9ls7KZaleNZOpNKqb4mq6jSrXEGHLFGW4t9jyY4yhaZhVWEBPqRFOP6GVROzu4w7RtXqm8wxpBpTWZwp9TECJ1J5YM0wVG2yCyqYkRcOP5umEHlpDOplOpb9pfXUlPf5P4EJyGchibdk8rXaIKjbJFVVOW2WQ1Ofn5CSkL44fE/SqnezRNj/eC71mLdk8q3aIKjeqyqrpG8skNuDzrgmCqqLThK9Q3O8XbuXo9GZ1L5Jk1wVI/tcvO0zZZ0JpVSfUdWURX9+wUR2y/Irc8NDfJnSEyYjvfzMZrgqB7LcuMmm605W42ydIaDUr2eJwYYO41KDNcZmz5GExzVY5lFVQT6C8Niw9z+bO0bV6pvMMaQWei+TTZbS0nQmVS+RhMc1WNZRZWMiAsnwN/9v046k0qpvqG4so6K2ka3r4HjNCpRZ1L5Gk1wVI9lFlWR4qFalc6kUqpvyPTQDConbS32PZrgqB6pbWhi34EajwUd0JlUSvUFzkqMpypTzplUumWD79AER/XIruIqjMFjA//AsT2EzqRSqnfLLKokMiSA+PBgjzzfOZNqp05o8Bm2JDgiMk9EdohIlojc28brd4nIVhHZKCKficiwFq81iUiG9bHEjvIo9/lu4S3P9IuDo2/cURYNPL2dxpq+K7OwitTECETct1p6a6kJ4WRpC47P6HGCIyL+wFPAmcA44AoRGdfqtPVAmjFmEvAm8FiL1w4ZY6ZYH+f1tDzKvTILq/D3E5Lj3D+Dykn7xvsGjTV9W1ZRlUe7wsGxwGB2SZXOpPIRdrTgzASyjDHZxph64HVgfssTjDFfGGNqrC9XAoNteK7yAplFlQzrH0ZwgL/HyuCcSaV9472expo+qrSqjtLqeo92hYPOpPI1diQ4SUBOi69zrWPtuQn4oMXXISKSLiIrReR8G8qj3CjTC2pVzplUmdpF1dtprOmjvltM1HNd4fBdV7xWpnyDWwcZi8jVQBrwpxaHhxlj0oArgb+KyMh2rr3FCk7pxcXFbiitOpr6xmb2ltZ4dPyNk86kUi11N9ZonPFOnp4i7pSS4NyTShMcX2BHgpMHDGnx9WDr2BFE5FTgfuA8Y0yd87gxJs/6Nxv4Epja1kOMMc8YY9KMMWnx8fE2FFv1VHZJFU3NxmMri7akM6n6BJfHGo0z3imzsJLw4AAGRoV4tByhQf4MjgnV1mIfYUeCswZIFZHhIhIEXA4cMUNBRKYC/8YRcIpaHI8RkWDr8zhgLrDVhjIpN9hR4HiTjx7g+RYcnUnVJ2is6aO2F1QyKjHcozOonEYlRGgXlY/ocYJjjGkE7gA+ArYBi40xW0TkYRFxzlT4ExAOvNFqiuZYIF1ENgBfAI8aYzTo+Iht+ZUE+gsj4ryjBQe0b7w301jTNxlj2F5QyZiBkZ4uCqAzqXxJgB03McYsBZa2OvZAi89Pbee6b4GJdpRBud+OggpGxocTFOD59SIHxzj3pNIEpzfTWNP3OLuex3hBSzE4xgE5ZlLVeHxWl+qY5/8yKZ+1o6DSK7qnQGdSKdVbbS+oAGC0h2dQOTnX3crUSQ1eTxMc1S3lNQ3sL69lzADvaDYGR81Ku6iU6l22W2P9vCXWOGdSZeoGv15PExzVLTsKnUHHO2pV4OgbL6io1ZlUSvUiOwoqGRgVQlRYoKeLAnw3k0qXpfB+muCobtnhbDb2ogRHZ1Ip1fts96KucCedSeUbNMFR3bK9oJKIEM+vS9GSzqRSqndpaGpmV1GV1yU4KYnhZJdU0agzqbyaJjg+pKK2gfX7DrJlf7nHpyhuL6hk7IBIr1iXwslbZlJV1zWSkVPG5rxy6hqbPFoWpboj50ANa/YcIK/skEfLsbukmvqmZsZ6yfgbp1EJETQ0GfaU1hz9ZBfaX3aINXsOsM/D5fBWtkwTV65VXFnHHz/czpKM/dRbiU3/fkHcflIK181Jxt/PvUmGMYadBZWcP7WjbYDczzmTakdhhUeeX1PfyOMf7+TVVfs41OBIbCJCArjumGR+dNJIwoL07aa82zeZxTyydDtb8797D81IjuGBc8YzcXCU28uz3YsWE23JOZNqR0GlR6aKb84r5zfvb2HNnoOHj40dGMm9Z47hhFG6AreTRlwvt3bvQX7wYjpVtY1cMXMIx6XGU13fyJtrc3n4v1tZkV3KP66YSkig+3bzzis7RGVdo9cFHYDxgyL5cEsBxhi3ti4VVdZyzbOr2VFYyUXTBnPG+EQamgxLN+Xz5BdZfLqtkP9cm8aQ2DC3lUmpzmpuNvzxo+38+6tshsf148FzxzE8rh87Cip5dtluLnr6W/50ySTmT3FvpWZHQQUBfsLIeO9abyY1MZwAP2HL/nLOnjTQrc9esmE/dy3KILZfEPedOYbRAyLYU1LNCyv2ct2C1dx6wgh+ccYY/Nxc8fVGmuB4sRW7Srlh4WoGRIaw6JbZR+yke97kQbzw7R5+89+t3Pl6Bv+8aprbfqG37HfU7sZ6ycqiLY1PiuL1NTnsL68lKTrULc+sqG3gyv+sYn/ZIV68cSbHt6hBnT1pIJfsKOInr63nsn+vYPEPj2FwjCY5ynsYY7jv7U0sSs/hqllD+fU54w5XmE4cncBlM4Zwy0tr+dmiDMKDAzhlbKLbyrZlfwUpCd6xmGhLIYH+pCZGsHm/e1uLP9layJ2vrydtWCzPXDud6LAgxwuj4cpZw/jN+1v491fZVBxq5A8XTPCqIQSe4F2/NeqwHQWV3PJSOkNiwnjztjlHJDcAIsL1c4dz/1lj+XBLAU9+keW2sm3JK8dPYJwXJjgTBjnKtDmv3C3PM8bw88Ub2F1SzbPXpR2R3DidODqBV38wm6q6Rq55brVOY1de5YlPM1mUnsMdJ6Xwu/MnfK81ODosiOevn8G4QZH85LX17C2tdku5jDFszitnQpL7u8Y6Y8KgSLbklWOMccvzdpdUc9eiDMYPimLhjTO+S24sQQF+/O78Cdx24kheW72Pxz/e6ZZyeTNNcLxQdV0jP3gxndBAfxbeOJO48OB2z73p2OGcN3kQf/8sk0257vmjvimvnJSEcEKD3Nct1lljB0bi7ydscVOC88baXD7eWsh9Z45hzsi4ds+bkBTFc9fPIPdgDXe+vp7mZvcERaU68snWQv7+WSaXpg3m7tNHtVvj7xccwDPXpOHnJ9y9eANNbvj9Layoo6Sq/nClxdtMSIqitLqewoq6o5/cQ83NhrsXZ+DvLzx99bR2x/OJCPecMZrL0obw5BdZfLi5wOVl82Z9tosqv/wQn28vYnt+JYcamogLD2bq0GhOGBXv1vEsbXnkg23kHKzh9R/MPmo3i4jw2/kTWLW7lHvf3siSO4516aBjYwyb8io4flT7f8w9KSTQn5Hx/dzSdFxaVccflm5jRnIMN84dftTzZyTH8sA54/j1e1t4+qtd3H5SisvL2JGymno+317ExtxyKmsbiQkLZOLgKE4cleA1i6r5uuZmQ/reg6zeXcq+AzX4iTA8rh/Hj4r3eBfvgep67nt7I2MHRvK78ycetTtjUHQoD88fz88WbeDV1fu4ZvYwl5Zvk1VJ8cTg5s6YkPRda/EAFy+X8erqfazbV8bjl0w+ahe3iPDw+ePZXljJ3YszGDfweIb292y3+Jb95SzLLGFPaTVNzYak6DDmpPRn2tAYl/696nMJzs7CSv700Q4+3VaIMY5ZLhHBARRX1dHQZIgOC+S2E0Zy3ZxkjyQ6X+8s5uWV+7j52OHMGtG/U9dEhQXyy7PG8tPXM3hrbS6XzhjisvIVVdZRUlXHRC9tNgaYMCiKZVklLn/Onz/eQXVdI3+4YGKnxz9dPXsYq3Yf4IlPdnLCqHiPNL+X1dTzl092sjg9h9qGZsKC/IkODaS0up66xmaCA/y4NG0IPz45hYRI71nnyJc0NRveXZ/H3z7LZN8BxxTehIhgmg2UVNXxyAfbmTo0mvvOHMvM4bFuL58xhl+9u4nyQw28dNOsTo9xOX9KEq+vzuEvH+/gvMmDiAp1XSK82eoK93Qi2J6xAyMRgc37yzl1nOvGJZXV1PPHD7czZ2R/LpzWuUHewQH+/POqacz769fc/UYGr99yjNtn2wKk7znAH5ZuY92+MgDiwoPwE6G4qo4nPoXk/mH86MQULp4+2CVjSPtMgtPQ1MzfP8vkqS+y6BcUwB0npXD+1CRGxPVDRKhvbGZldikLlu/mkQ+28876PJ68ciopCe6bKVR+qIFfvLWRkfH9+PkZo7t0rXPQ8WMf7eCcyQNdNiXZ2Q3mrf3i4Bho/Pb6PIoqa0mIcM0f6N0l1SxOz+Wa2cO+Nz6qIyLC786fwJo9B7hrcQZL7jjWrYn01zuLuWtxBgdrGrh42mCumj2U8YOi8PcTmpsNG3LLWLQmh9fX7OPdjDx+dfZYLk0b0ucHK3bF3tJqfvp6Bhk5ZUxMiuKvl03hlLEJRIQ4koHiyjr+u3E///4qm0v/vYIb5w7nF2eOJjjAfb8H72/MZ+mmAu6ZN7pLCYSI8MC54zjnH8t48vNM7j97nMvKuDmvnJHx4V67vEJYUAAj48PZnOfa1uJ/f51NVV0jD5w7rkvvw6ToUH5z3njuWryBZ7/J5tYTRrqwlEeqb2zmD0u3sfDbPQyKCuHBc8dx9qSBh+NxRW0DX2wv4rllu7nnrY0sSs/hsYsn2T5brk+MwSkor+WSf63gH59nceG0wXx1z0ncffpoRsaHH/6FCQrw4/hR8Sy8YSYLrk+juLKO855czlc7i91Wzoff30pRZR1/uXRKl//oiQj3nz2Wkqo6Xl21z0UldDQbi5cOMHZy9tlvcWE31ROf7CTI369b3UzRYUE8dvFkdhZW8ZdP3DcQ8D9fZ3P986uJCw/m/TuO5Y8XT2LS4OjDNTs/P2Hq0BgevWgSH915POMHRfKLtzZx1+INHKrXBQs74/0N+znrb9+QXVzFE5dN5r3b53L+1KTDyQ1AfEQwN8wdzhc/P5Hr5ySzYPlurvrPKspr3DP4vLCill+/u5mpQ6O55bgRXb5+/KAoLpiaxEsr91Jc6brxJ5u8eICx04RBkWzZ77rxfkWVtSxcvofzJg/q1majF0xNYt74ATz+8U52FLhnC5sD1fVc/ewqFn67hxvmJvPp3Sdww9zhR1Q2I0MCmT8lifdun8vjl0xmV3EV5/1jGUs35dtall6f4GzdX8H5Ty0nq6iKp66cxp8vmUxsv6AOrzl5TCJLf3ocw/r346aFa3gvI8/l5fx4SwFvrcvl9hNHMnlIdLfuMX1YLHNT+vOvr7KpbXDNH6Qt+x21qn7B3lmrAhjnTHBcNNB4Z2ElSzbs54a5ycRHtD8AvCMnjIrnqllD+c832aTvOWBzCb/vma938ful25g3YQBv/2jO4Z9Re0bEh/PqzbO567RRvJuRx0VPf0thRa3Ly+mrjDE8+XkmP35tPeMGRfLhncdzwdSOm91Dg/x56Lzx/OOKqWzMLeeSf39LkYt/xsYY7n1rI3WNTTx+yWQC/Lv3J+COk1Kob2zm2W+ybS6hQ1FFLUWVdd6f4CRFkV9eS0mVaxK9f32ZTX1TMz87dVS3rhcRfn/BBCJCArj7jQyXr4BfWdvAdQtWsyG3jL9dPoUHzx3fYQuciHDR9MF88NPjSE2M4EevrOPxj3fYNjPNlgRHROaJyA4RyRKRe9t4PVhEFlmvrxKR5Bav3Wcd3yEiZ9hRHqcvdhRxyb++RQTe+OExXVqQKTEyhEW3zmb6sBjuWrzBpaPRD1TX88t3NjFuYCR3nJzao3v9+ORUSqrqeG21/a04jgHG5V47q8EpIiSQEXH9yMgpc8n9n/tmNyGBfvygG7Xflu47ayxJ0aH8/I0N1NQ32lS671ucnsMflm7n7IkD+ccV7c/AaM3PT/jJKaksuG4Ge0urueCp5R7fQdkbY01DUzO/eGsjf/54JxdMTeLlm2cxqAtrMJ07eRALb5xB7sFDXP3cKg5W19tVtO9ZnJ7DFzuK+cW8MYzoQXfAiPhwzp08iJdW7uWAC8q72WoV8fZY40zANrgg1lTUNrBozT7OmzyI5Lh+3b5P//Bgfn/BBDbnVfDPL3bZWMIj1TY0ccuLa9maX8HTV0/r0qKQA6NCWXTrbC5NG8w/Ps/i7jc2UN/Y82SsxwmOiPgDTwFnAuOAK0SkdcfsTcBBY0wK8ATwR+vaccDlwHhgHvBP63499unWQm5+IZ3kuH68e/vcbg1UiwwJZMH1M5g0OIofv7bOJd1VLQf7/eWyyT1e0Gr2iP7MSI7h2W92274R3P7yWgor6pg6NMbW+7rCtGExrNtXZvsaFQeq63k3I48Lpg4m5igtgUcTHhzAny6ezJ7SGh77cIdNJTzSR1sKuPetjRyXGsdfLpvcrYGGJ41JYNGtx9DQbLj46W89tlu7t8aaO15dx+L0XH5ySip/uXRyt8bSzBkZx7PXprGntIbrnl9NZa393VU5B2p4+P2tHDOiP9cdk9zj+91xUgo19U28snJvzwvXyrq9Zfj7idfOoHKabHXxrtt38Ognd9HiNTlU1zd1aobm0cybMJD5Uwbxj88zXbJGWGNTMz95bT0rskt5/JLJnDym64OugwP8+eNFk7jz1FTeXpfHj15Z2+P4bUcLzkwgyxiTbYypB14H5rc6Zz7wgvX5m8Ap4hj8Mh943RhTZ4zZDWRZ9+t5oUbEcu0xw1h86zEk9mAmSL/gABZeP5OUhAh++NJa1u619xfZOdjvZ6eN6lYfa1tuOnYEeWWH+GRroS33c3J+79OH+UCCMzSGA9X17LV5E7rXVu+jrrGZG+Ym23K/Y0b25/o5ySz8dg8rdpXack+nFbtK+fFr65k0OJp/XT29R4NYJyRF8fZtc7hw2mCS+3e/NtlDXhlrLpsxhD9fMpm7Tmt/HZnOmJMSx9NXTWPr/gp+8GK6rd3Mzc2Ge97ciIjw2MWTbJmxkpoYwQmj4nlx5V5batstrd17kHEDI712gLFTaJA/4wZGsm5vma33bWo2vLBiD2nDYmxL8n5z3nhi+gXxc5taR5yMMfzynU18vLWQB88d16M9CkWEO08dxWMXTeLCaYN7PLnBjgQnCchp8XWudazNc4wxjUA50L+T1wIgIreISLqIpBcXH70lJTIkkAfPHW/LWJGosEBevHEmiZHB3LhwjW3N9Pnlh/jVO5u6PdivPaeNS2RIbCgLlu+27Z4A6/YeJDTQnzFeuAdVa84kzM6EtKGpmZdW7OXYlLjDm+3Z4Z55o0nuH8b/vbmBqjp7uqo25ZbzgxfTGRYbxvPXz7DlfTAkNoyHzhvf7XEbNnB5rOlqnAHHmL2Lpw/u7PfQoVPGJvLnSyazMvsAP319vW2tsAuW72ZFdim/Onusrfuh3XjscIor6/jfpv223bOxqZmMnDKfqEiBI9Zk5JTZ2mL+2bZCcg4c4gYbWm+cosOCePTCiWwvqOTvn2Xadt9HP9h+uAXTrvJeOmMIZ03s+R5fPjPI2BjzjDEmzRiTFh/v/t1S4yOCD68Xce1zq8k92LOWgeZmw8/f2EBDk+Evl06x9Y+Gv59w/ZzhrNlzkI25Zbbdd+3eg0wZEu3JP3CdlpoQTkRwAGttbDr+YHMBBRW1trXeOIUFBfDnSyaTV3aIPyzd1uP77Squ4rrnVxMVGshLN83qcVdaX+LpOANw/tQkHjx3HB9tKeT+dzb3uJl+R0Elj320g1PHJnKZzWtkHZ8aR0pCOM8t221bd/D2Asfiq9N8JMGZNiyGQw1Nh3c+t8Pzyx3Tq88Yb+/6OqeMdSTjT3+1y5ZxQ//6ahf//jqba48Zxs9O7dn4UVew4y9VHtDyXTPYOtbmOSISAEQBpZ281msMiQ3jxRtnUl3fyLXPraa0ByPnFyzfzfKsUh6wdu2126VpgwkPDuD55XtsuV9NfSNb8yt8plbl5ydMGRrNOhtbcJ5fvpvk/mGcNDrBtns6pSXHcvOxw3l11T6+7sFYr/zyQ1z73GoEePnmWS5fYdXN+kysuWHucO44KYVF6Tn86aPuj8+qa2zizkUZRIYE8OhFR1+tuKtEhBvmJrM5r4I1e+x5rznHs/hKrJk2NBrAtnE42/IrWJFdyjXHJLukMvnrc8YRHx7M3W9s6FE36Our9/HoB9s5b/IgHjp3vFeulWXHT28NkCoiw0UkCMdAviWtzlkCXGd9fjHwuXGk+0uAy62ZD8OBVGC1DWVymbEDI1lw/Qzyyg5xw8I13epSWJVdyqMfbOe0cYlc7qJVhyNCArl4+mD+u3G/LVNPN+aW09RsfCbogCNA7iistGXAZkZOGev3lXHdnGSX7druWJupH3e/sYH88kNdvr64ss6xnsqhBl64caZLEmcP61Ox5u7TR3HlrKH888td3ZqObYzhV+9sZlt+BX+8aFKHe9r1xIVTBxMVGsiCZfZ0ia/de5ABkSEM8pHkPCk6lMTIYNu6wxcu30NIoB9XzHTN34ao0ED+ePEksoqqePC9Ld1qeXsvI4/73tnEiaPj+fMlk10WE3uqxwmO1c99B/ARsA1YbIzZIiIPi8h51mnPAf1FJAu4C7jXunYLsBjYCnwI3G6M8foVxWYkx/LPq6axZX8Ft76UTl1j54uce7CGH72yjqGxYfz5kskuzXqvn5NMY7PhZRsW/lu9+wAiMNWqrfiCtGGxGAPpNgSe55fvJjw4wLaxFm0JCfTnn1dNp8babLUri+sdrK7nmudWkV9ey/M3zPD69UO6o6/FGuc+c2dOGMDv/reNt9bmdun6hd/u4Y21ufzk5BROGeu6rQRCg/y5fOYQPt5a0OOue2MMq3cfYPqwGK9sEWiLiJA2LJbVuw/0uJuu5SzN1ruF2+mEUfGHWwi72sr/0ZYC7lq8gZnJsTx91fQez/x1JVtKZoxZaowZZYwZaYz5vXXsAWPMEuvzWmPMJcaYFGPMTGNMdotrf29dN9oY84Ed5XGHU8Ym8thFk1ieVcrtr6zr1DomBeW1XPXsKuqbmnnm2uku3ccFIDmuHyePTuDVVXu7lIS1ZVlWCeMHRbr0TWe36cNiCPL349se7ktVWFHL/zbmc0na4CNWpHWF0QMi+PsVU9myv4JbXurcTJr9ZYe47JkVZJdU8+x1acxIdv/eRu7S12KNv5/w18unMGdkf+55ayPvru9cr9qba3N5+L9bOW1cInd2c5G4rrj2mGREhJdW9GzKeHZJNfnltcxJ6dw+fN7imJH9yS+vZXdJdY/uY/cszY7cddoozhifyO/+t7XTyfPb63K5/ZV1TBocxXPXzyA0yLMbUx+N96ZePuCi6YP57fzxfL69iEv+tYK9pe3/cm8vqOCSf39LSWUdL9w40217XN0wdzglVfW8v6H7S2DX1Deyft9B5o70zh3E2xMa5E9acgzLsno2/frllXtpMobr5yTbU7CjOGVsIn+8cBLLskq4dsHqDpfDX5ldygX/XE5+WS0Lr5/B3BTf+j9SRxcc4M8z16aRNiyGOxdl8NiH29ud5muM4T9fZ3PPmxuYOzKOf1wx1S3dB0nRoZwxPpHXVu/r0aKVzsrIsT72e+ws7/IeVKZcNUuzPX5+wl8vm8oxI/vz8zcd+1W11wJV39jMHz/c7mi5GR7LCzfOJNyLV7N30gSnh645JpnnrpvBvtIazvjr1zzxyc4j/iAdqK7nr5/uZP6Ty6lraOaVH8xmmhsXypub0p9RieE8v7z7sxxW7z5AQ5Nhjo8FHYC5KXFsy6/o9lLqtQ1NvLpqH6eMSWCYG9d/uXTGEP562RQ25JRx5t++4fXV+47ostpVXMUv3tzIFf9ZSWigP2/cdoxP/v+ozgkPDuClm2Zx+Ywh/PPLXZz35DI+2lJweGqyMYaMnDKuXbCa3y/dxhnjB/Cfa9PcupHrDXOHU1HbyNvruj92e1lWCUnRoQy1cSq7OwzrH0ZSdCjLepDguGqWZkdCg/x57roZnD4ukd/9bxvXLljNhpzvFkitb2zmoy0FnPfkMp7+cheXzxjCwhtmEunilmy7eH8K5gNOGpPAx3cdz2+WbOVvn2Xyt88yGdY/DD8R9pZW02zg7IkDefDccST0YNHB7hBxTBn/5TubWLPnIDOHd7374ttdpQT5+zEj2XcGGDsdmxLHnz7awbe7Sjlv8qAuX78kYz+l1fW2rkfRWfOnJDF6QAT3vrWJe9/exINLtjAkNozqukbyy2sJ8vfj+jnJ/Pz00V69N5iyR1CAH49eNIlTxibym/e3cOtLawkL8mdwTCgHquspqaonIiSA35w3nmuPGeb2MSxpw2KYkBTJwm/3cNWsoV1+flOzYcWuUuZNGOAz42+cRITjUuP436Z8mppNt1YMX7DMdbM0OxIS6M+/rp7Oiyv28pdPdjL/qeXEhQcTExbI/rJDVNc3MTQ2jH9dPZ15Ewa4tWw9pVHRJgOjQvnXNdPJKqriw835bC+oxBjHPjNnTxzIaA8ujnfB1CT++OF2nl++u1sJzhfbi5g+LMbrVxVty4SkKKJCA/l6Z3GXExxjDAuW72bMgAjmjPTMmIAxAyJ550dzWJFdyufbisg9eIiwIH8mDY7izIkDe7RKt/JNp41L5KTR8Xy+vYhvd5VSWFHL5MEBTBsWw9mTBnqsdi0i3DBnOHe/sYFvMks4flTX1hFav+8gFbWNHJfqmfWHempuShyvr8np1iKFa/ceJCOnjN+cN94jM5JEhOvmJHP+1CQ+3JzPmj0HqaxtYM7I/hybGs+Jo+MJ9IH1z1rzvb9YXi4lIbzHG2bazTnL4T9fZ5N7sIbBMZ1v/t1dUk1mURVXzBzqwhK6jr+fcNLoeD7bVkhjU3OX1pVYnlXK9oJKHrt4kkdrlCLCnJFxzPGxMVDKdQL8/Th9/ABOH+9dNepzJg/kkQ8clamuJjgfby0k0F84cbRvJjjHp8YT4Cd8vLWgywnOgmW7iQxx7SzNzogKDeSyGUO5bIZvxvvWfC8lU93S3VkOn2x17KJ+2jjXTTN1tXkTBnCwpoHVuw906brnlmUTFx7Ura4tpfqi4AB/rpo1lC92FJNdXNXp64wxfLylgGNGxrl8pqKrRIUFcszI/ny4uaBL4x1zD9bwweZ8rpg1VLuabaYJTh/R3VkOH20pZNzASFv3r3G3E0YlEBrozwebCzp9TVZRFV/sKObq2cPcOlBTKV931eyhBPoLL3ahMrWzsIo9pTWc7sMVKYAzJwxkb2kN2/I7v23DwuV7HF1ENuzwro6kCU4f4pzlsHhNztFPBvaUVLN270HOntTzTc88KTTInxNHx/Nhi1knR/PUF1mEBPpx9exhLi6dUr1LQkQI504axBvpORyoru/UNW+vy8XfTzjDy7rcuur08Yn4CZ3efLSkqo5XVu3j3EkDGRQd6uLS9T2a4PQhacNimDk8lqe+3NWpVXLfWpeLn8BF0zzbL2yHC6YmUVxZx2fbi4567q7iKt7LyOPaY5Jdtry9Ur3ZbSeOpKahiX9/teuo5zY2NfP2+jxOGp1AfIRvv9/iwoM5YVQ8b6Tn0tCJytQzX2dT19jEj0/xrnGbvYUmOH2IiPB/Z4ymuLKOF1bs6fDchqZm3lyby3Gp8b1iw8aTxyQwIDKEVzqxbcXfPs0kOMCfW44f4YaSKdX7pCZGcMGUJBZ+u4fCo+yF9/n2Ioor67gkzfcrUgBXzhpGUWUdn23ruDJVVFnLiyv2MH9KEiPjw91Uur5FE5w+ZkZyLCeMiufpL3d1uPjdexn7yS+v5bo5vaOLJsDfj8tnDuGbzGIyC9vvH0/fc4AlG/Zz47HaeqNUT/z01FSamg2Pf9z+bujGGP711S6SokM5eYx7139xlZNGxzMwKoQFR1lc9Y8f7KCp2fATbb1xGU1w+qBfnT2WmvpGfvvfrW2+Xt/YzD+/yGLMgAi3LzrlStcek0y/oAD+8snONl+vb2zm1+9tYWBUCLeflOLm0inVuwzr34+bjh3O4vRcVuxqe7uU5VmlrNtXxq0njPDJdVbaEuDvxw9PGMnq3QfaXdl49e4DvLUul5uPG8HwOPetkN7X9I7fKNUlqYkR3HZiCu9l7Oe9jO8vq/7ssmyyS6r5vzNG+9yKoh2J7RfETccO54PNBXy1s/h7r//54x1sy6/gofPG++Sihkp5mztPHcXQ2DDueWvD9wYc1zY08eCSzQyNDePStCEeKqFrXD5zCEnRofzm/a3f2zC3vKaBny3KYEhsKHdoRcqlNMHpo+44KYWZybHc8+ZGvsn87o/9N5nF/OXjncwbP4BTxvr2lM223HbiSFITwvn5GxvYY+38a4xhwbLdPPN1NlfPHurzMzmU8hahQf787fIpFFbU8YMX0ymrcSQ5Tc2G+97exK7iah6eP77XLcUQHODPIxdOJKuoil++vYmmZkdXVfmhBm58YQ1FlbX844ppuu6Ni0l3N2D0pLS0NJOenu7pYvi80qo6rnp2FZlFVZw1cSDBAX68uz6PEfH9ePO2OT6zoVpX7Sys5PJnVtLY1MwFU5PILqnmm8wSTh+XyFNXTes1TeWeJiJrjTFpni5Hd2mcsc/STfn89PX19O8XzJkTB7B+XxkZOWXcfdqoXj2D6O+fZfKXT3YyZUg004bGsHRTPsVVdTx5xVTOnOjby294k/ZiTY8iuYjEisgnIpJp/fu99alFZIqIrBCRLSKyUUQua/HaQhHZLSIZ1seUnpRHdU3/8GDevG0O18wexrLMYj7aXMBF0wbzxg97b3IDMCoxgrdum0NaciyL0nPILq7mvjPH8PTV0zW58VIaa3zbWRMHsujWY0iOC+OVVfuoONTA45dM7tXJDcBPTknl8UsmU3GogZdX7mVo/zDe/OExmty4SY9acETkMeCAMeZREbkXiDHG/KLVOaMAY4zJFJFBwFpgrDGmTEQWAv81xrzZledqzUop72dnC44nYo3GGaV8g0tacID5wAvW5y8A57c+wRiz0xiTaX2+HygCfHM3NaWUp2isUUp1SU8TnERjTL71eQHQ4ahUEZkJBAEtl7f8vdWc/ISItLvwiIjcIiLpIpJeXPz9GTBKqV7NLbFG44xSvcdRExwR+VRENrfxMb/lecbR19Vuf5eIDAReAm4wxjjXsL4PGAPMAGKBX7RzOcaYZ4wxacaYtPh4rZQp1dt4Q6zROKNU73HUOWrGmFPbe01ECkVkoDEm3woqba5NLSKRwP+A+40xK1vc21kjqxOR54Gfd6n0SqleQ2ONUspOPZ2EvwS4DnjU+ve91ieISBDwDvBi6wF+LQKW4OhT39yZh65du7ZERPZ2s8xxQNvLS7qXluNIWo4j9YZy2LnPh9tjTSfjjDv/n/RZvvUsdz+vLz+rzVjT01lU/YHFwFBgL3CpMeaAiKQBPzTG3CwiVwPPA1taXHq9MSZDRD7HMQhQgAzrmqpuF6hzZU73hrU5tBxaDi1Hl8rhlbHGnT8ffZZvPcvdz9NnfV+PWnCMMaXAKW0cTwdutj5/GXi5netP7snzlVJ9g8YapVRX6apmSimllOp1+mKC84ynC2DRchxJy3EkLYdvcOfPR5/lW89y9/P0Wa345F5USimllFId6YstOEoppZTq5TTBUUoppVSv02cSHBG5xNpluNmaWuo8niwih1rsMvwvT5TDeu0+EckSkR0icoYry9HquQ+JSF6Ln8FZbnz2POv7zbI2UfQIEdkjIpus799tOyyKyAIRKRKRzS2OHXXnbDeVw2O/F97uKO/jSfLdruabRCTEFc8SkdNEZK31jLUiYutMMXHszr7S+Z4Qx/YXLiUid4uIEZE4F9zbrbFGRPxFZL2I/NfFz/mZ9fuxWURe6+nvWxv3bys2/ElEtotj65N3RCTaVc+yjv/Yet4WcWy82znGmD7xAYwFRgNfAmktjicDm72gHOOADUAwMBzHHjr+birTQ8DPPfB/4m99nyNw7Bu0ARjnod+PPUCcB557PDCt5e8g8Bhwr/X5vcAfPVQOj/xe+MJHB+/jAGAjMNn6un9P38cdPGsqMMj6fAKQZ/P3+DFwpvX5WcCXLv6ZDgE+wrHOka3vRU/EGuAu4FUcu9i76hlJwG4g1Pp6MY61n+x8Rlux4XQgwPr8j3bFqHaedRLwKRBsfZ3Q2fv1mRYcY8w2Y8wOLy7HfOB1Y0ydMWY3kAW4vMbkYTOBLGNMtjGmHngdx8+hzzDGfA0caHX4qDtnu6kcqh0dvI9PBzYaYzZY55UaY5pc8SxjzHrj2DUdHIsbhkoHGxZ359FApPV5FLC/g3Pt8ARwDx3sM9YDbo01IjIYOBt41lXPaCEAx/99ABCGzf9PbcUGY8zHxphG68uVwGBXPQu4DXjUGFNnndPmNi1t6TMJzlEMt5oSvxKR4zxUhiQgp8XXudYxd7nDam5c4I4uEYunv+eWDPCx1dR/i4fK4NSlnbNdzBO/F75sFGBE5CMRWSci97jpuRcB65x/BGxyJ/AnEckB/oxjw1KXEMeGqnnOxNAF3B1r/oojWWs+ynk9YozJw/F/sw/IB8qNMR+78pltuBH4wIX3HwUcJyKrrL/RMzp7YU/3ovIqIvIpMKCNl+43xnxv7xpLPjDUGFMqItOBd0VkvDGmws3lcKmOygQ8DfwWxx/53wKP4/il7UuONcbkiUgC8ImIbLdqEx5ljDEi4qm1HPr070U338cBwLE4di2vAT4TkbXGmM9c8CznteNxdBOc3tF5XX0ujpWjf2aMeUtELgWeA9rdELWHz/ol3Si/NxKRc4AiY8xaETnRxc+KwdESNRwoA94QkauNY1VvlxOR+4FG4BUXPiYAiAVm43hfLRaREcbqrzrahb2G6WA34g6uqQOcTV9rRWQXjoyx2wNNu1MOIA9HH7TTYOuYLTpbJhH5D+DSQXEtuPR77gqrJoQxpkhE3sHRpO2pBKdTO2e7mjGm0Pm5m38vvEI338e5wNfGmBIAEVmKY0xBhwlON5/l7Ap5B7jWGLOrq9d39FwReRH4qfXlG/Swu6W9Z4nIRBx/oDeICDjiwDoRmWmMKejJM1twZ6yZC5xnDcoPASJF5GVjzNUueNapwG5jTDGAiLwNzKGdLUvsJCLXA+cAp3Qm2eiBXOBt6xmrRaQZxwacxUe7sM93UYlIvIj4W5+PAFKBbA8UZQlwuYgEi8hwqxyr3fFg64+o0wV0cld3G6wBUkVkuDh2gr4cx8/BrUSkn4hEOD/HUZN018+gLc6ds6GdnbPdwYO/F77sI2CiiIRZYyJOALa64kHWzJX/4RiQvtwFj9iPo/wAJwOZLngGxphNxpgEY0yyMSYZxx+0aTYmN+DGWGOMuc8YM9j6Xi4HPndRcgOOrqnZ1u+b4Gh12+aiZx0mIvNwdMGdZ4ypcfHj3sUx0BgRGYVjkHjndjK3Y+SzL3zgCNC5OFprCoGPrOMX4RiglwGsA871RDms1+7HMdJ/B9bsBTf9bF4CNuGY/bEEGOjGZ58F7LS+7/s99LsxAsesig3W74LbygG8hqObtMH6vbgJx8ybz3D8QfkUiPVQOTz2e+HtH0d5H19t/R5tBh5z1bOAXwHVVuxyfnR6hkknnnsssNZ6X6wCprvpZ7sHF8xo9ESsAU7EhbOorGf8Bthu/b69hDXbyMb7txUbsnCMaXL+3v3Lhc8KwtEitdn6G31yZ++nWzUopZRSqtfp811USimllOp9NMFRSimlVK+jCY5SSimleh1NcJRSSinV62iCo5RSSqleRxMcpZRSSvU6muAopZRSqtfRBEcppZRSvY4mOEoppZTqdTTBUUoppVSvowmOUkoppXodTXCUUkop1etogqPaJCJGRFI6eH2LiJzYyXvtEZFT7SqbUsp3iUiViIyw+Z4nikiunfdUvk8TnF7ISijqRSSu1fH1VuKS3MX7LRSR37U8ZowZb4z5suelPeI5yVb5Auy8bwfPe0hEXnbHs5Tqi6xYdMhKaqpEpAoYZYzJdsNz3VKp0uTKe2mC03vtBq5wfiEiE4EwzxWn93FXIqaUjzvXGBPe4mO/pwvkTTSOuI4mOL3XS8C1Lb6+DnjR+YWIfCkiN7f4+noRWdb6JiJyC3AVcI9VA3vfOn64hmS1hLwpIotEpFJE1onI5LYKJSJ+InKviOwSkVIRWSwisUf7ZkRkkIgsEZEDIpIlIj9o8Zq/iPzSumeliKwVkSHWa38TkRwRqbCOH2cdnwf8ErjM+r42dOI5zu/zZRGpAK4/WrmVUkdydn+LSJCIZIjIj63j/iKyXEQesL4eJCJviUixiOwWkZ+0uEeo1bJ8UES2AjM6+exgEfmriOy3Pv4qIsEtXp9vlanCiifzrOM3iMg2K75ki8it1vF+wAfAoBatVIM6eo6zxUdEfiEiBcDz9vxkVWua4PReK4FIERkrIv7A5UCXu2OMMc8ArwCPWbWvc9s5dT7wBhALvAq8KyKBbZz3Y+B84ARgEHAQeKoTRXkdyLWuuRj4g4icbL12F47WqrOASOBGoMZ6bQ0wpUW53hCREGPMh8AfgEXW9zW5E89xfp9vAtE4fi5KqW4wxtQDVwMPi8hY4F7AH/i9iPgB7wMbgCTgFOBOETnDuvxBYKT1cQaOClxn3A/MxhETJgMzgV8BiMhMHJXA/8Px/j4e2GNdVwScgyO+3AA8ISLTjDHVwJnA/lYtVO0+xzIAR0waBtzSybKrLtIEp3dztuKcBmwD8lz4rLXGmDeNMQ3AX4AQHG/w1n4I3G+MyTXG1AEPARd31ExrtcbMBX5hjKk1xmQAz/JdC9XNwK+MMTuMwwZjTCmAMeZlY0ypMabRGPM4EAyM7uZzAFYYY941xjQbYw516iejVN/2roiUWR/vtnzBGLMZ+B3wLvBz4BpjTBOOFpl4Y8zDxph6a8zOf3BU1AAuBX5vjDlgjMkB/t7JslwFPGyMKTLGFAO/Aa6xXrsJWGCM+cR6f+cZY7Zb5fyfMWaXFV++Aj4GjuvmcwCagQeNMXUaR1xH+/56t5eAr4HhtOiecpEc5yfGmGZr0N2gNs4bBrwjIs0tjjUBiR3cexBwwBhT2eLYXiDN+nwIsKutC0Xk5zgC1yDA4KiBxbV1bieeAy2+T6VUp5xvjPnU+YWImFavvwD8HnjLGJNpHRuGo9unrMV5/sA31ueDOPK9uLeTZRnU6ty9fBenhgBL27pIRM7E0Wo0CkfDQBiwqZvPASg2xtR2ssyqm7QFpxczxuzFMdj4LODtVi9Xc+Sg4wEd3aoTjxvi/MRqXh4MtDWYMAc40xgT3eIjxBjTUevSfiBWRCJaHBvKdy1SOTiaqo9gjbe5B0dtL8YYEw2UA9LO93W057R1jVKqZ/4J/Bc4Q0SOtY7lALtbxYkIY8xZ1uv5tIg5ON6nnbEfR/LU8jpnnGovjgQDbwF/BhKtOLKU9uPI0Z7T3jXKZprg9H43ASdbfcUtZQAXikiYONa7uamDexQCR1u3YrqIXGh1Nd0J1OEYB9Tav3D0sQ8DEJF4EZnf6pxgEQlxfuBIML4FHrGOTbLK6xxT9CzwWxFJFYdJItIfiAAagWIgwBq8GNnq+0q2EjKspu6OnqOUspGIXANMxzFg/yfACyISDqwGKq2BuKHWAOQJIuIcTLwYuE9EYkRkMI6xfa0FtowjVmx6DfiVFXfigAf47v39HHCDiJwijskQSSIyBgjC0bVdDDRarTmnt3hOIdBfRKJaHOvoOcpNNMHp5ax+4/Q2XnoCqMfx5nyBjgfMPgeMa6sPvYX3gMtwDBq+BrjQGo/T2t+AJcDHIlKJIwma1eqcKuBQi4+TcQwiTsZRC3oHR/+1s9n7LzgC3sdAhVXeUOAj4ENgJ44m4lqObNZ+w/q3VETWWZ939ByllE1EZCjwV+BaY0yVMeZVIB14whqHcw6OQbq7gRIcFRlnEvEbHO/p3Tje9y+18YilHBlHHsIx3icd2Iiji2mddQxjzGqsAcQ4Wnq/AoZZXdY/wRFjDgJX4ohhWNdtx5HQZFsxclBHz1HuI8ZoS5nqGRF5CEgxxlzt6bIopZRSoC04SimllOqFNMFRSimlVK+jXVRKKaWU6nW0BUcppZRSvY5PLvQXFxdnkpOTPV0MpVQH1q5dW2KMifd0ObpL44xSvqG9WOOTCU5ycjLp6W3NfFZKeQsR6ezqsl5J44xSvqG9WKNdVEoppZTqdWxJcERkgYgUicjmdl4XEfm7iGSJyEYRmdbitetEJNP66OyOsEqpPkbjjFKqK+xqwVkIzOvg9TOBVOvjFuBpABGJxbGB2Swc28k/KCIxNpVJKdW7LETjjFKqk2xJcIwxXwMHOjhlPvCitdX8SiBaRAYCZwCfWFveHwQ+oeMApnqZj7cUcNWzK7n5hXQ255V7ujjKi2mcUd11qL6JRz7YxoX/XM4jH2yjpr7R00VSbuCuMThJHLkHUK51rL3j3yMit4hIuoikFxcXu6ygyn3eSM/hlpfWknfwEBk5B7no6W9Zv++gp4ulfJfGGfU9DU3NXPf8ap75OpsmA898nc31z6+hrrHJ00VTLuYzg4yNMc8YY9KMMWnx8T4781RZ9pRU8+v3NjM3pT8f/ex4PrzzeBIig7lzUQa1DRp4lGdonOl9nvw8i9W7D/D4JZN57/a5PHHpFFbvPsC/vsz2dNGUi7krwckDhrT4erB1rL3jqpf7yyc7EYS/XDqF4AB/4sKDefTCSewtreGFb/d4unjKN2mcUUcorqzjma+zOWfSQC6cNhiA86cmcfbEgfzzyyyKKms9XELlSu5KcJYA11qzHGYD5caYfOAj4HQRibEG/Z1uHVO92O6Sat7fuJ/r5yaTGBly+PjclDjmpvRnwfLd2nysukPjjDrCs8uyqW9q5u7TRx9x/OdnjKa+qVkrU72cXdPEXwNWAKNFJFdEbhKRH4rID61TlgLZQBbwH+BHAMaYA8BvgTXWx8PWMdWLvb56H34i3DA3+Xuv3XL8SAor6vhwc4H7C6a8msYZ1RX1jc28mZ7L6eMSGR7X74jXhsf144xxA3h55T6tTPVitqxkbIy54iivG+D2dl5bACywoxzK+9U3NvPWulxOGZNAQkTI914/LiWOpOhQ3lqXx/wpbY4DVX2UxhnVFZ9uK6S0up7LZgxp8/XLZw7hwy0FfLG9mHkTBri5dModfGaQseodlu8qoaSqnkvS2g46fn7C+VMHsSyzmKIK7R9XSnXPu+vzSIwM5rjUtgeLH5sSR1x4MO+sz3VzyZS7aIKj3OqTrYWEBflzXGpcu+fMn5JEs4FPthW6sWRKqd7iUH0TX2cWc8b4Afj7SZvnBPj7cc6kgXy5o5hD9dpN1RtpgqPcprnZ8MnWQk4cHU9IoH+756UmhDM0NozPtxW5sXRKqd5iWVYJtQ3NnD6u466nU8cmUtfYzLe7StxUMuVOmuAot9mQW0ZxZd1Rg46IcPKYBJZllWjNSinVZR9vKSAiJIBZI2I7PG/m8Fj6Bfnz2XatTPVGmuAot/kmswQROGHU0RdQO3lMAnWNzazI1pqVUqrzjDF8k1nCcalxBPp3/CcuKMCP40fF8/m2Ihxj1FVvogmOcpsVu0oZOyCSmH5BRz135vBYggL8WLGr1A0lU0r1FntKayioqGXOyPbH+bV0XGo8BRW17CmtcXHJlLtpgqPcorahibX7DnLMyP6dOj8k0J+pQ6JZma3LlSilOs9ZKepsrJltdWOtzNbKVG+jCY5yi3X7DlLf2MycTgYdgFkj+rNlfzkVtQ0uLJlSqjf5dlcJCRHBjGi1uF97hsf1Iz4iWBOcXkgTHOUWK3eV4icwY3jHg/5amj0ilmYD6Xu0FUcpdXTGGFZmH2DOyP6ItD09vDURYfaI/qzMLtVxOL2MJjjKLVbvOcD4QVFEhgR2+pppQ2MI8vfTbiqlVKfsLqmmpKqOWSM631IMjspUYUWdjsPpZTTBUS7X1GzYmFvOtKHRXbouJNCfiYOjWLf3oGsKppTqVTJyygBH5agrZiQ7WpY11vQumuAol9tZWElNfRNTupjgAEwZEs2mvHIamprtL5hSqlfJyCmjX5A/KQnhXbpuZHw44cEBhxMk1TtogqNczhk0pgzpWq0KYPKQaOoam9lRUGlzqZRSvU1GThmTBke3uz1De/z9hIlJUZrg9DKa4CiXy9hXRnRYIMn9w7p87dQh0Y57aOBRSnWgtqGJbfkV3WopBpgyNJpt+RXUNujq6b2FJjjK5TJyypg8OLrTsxpaGhwTSmy/IE1wlFId2rK/goYmwxSrUtRVkwdH09hs2LK/wt6CKY+xJcERkXkiskNEskTk3jZef0JEMqyPnSJS1uK1phavLbGjPMp7VNU1srOosttBR0SYMiSaDZrgKDTWqPY5K0FTuxlrplotPxpreo+Ant5ARPyBp4DTgFxgjYgsMcZsdZ5jjPlZi/N/DExtcYtDxpgpPS2H8k4bc8swhm43G4OjZvXFjiIqaxuI6MI0c9W7aKxRHcnIKWNQVAgJkSHduj4xMoQBkSHaWtyL2NGCMxPIMsZkG2PqgdeB+R2cfwXwmg3PVT5gq9XcOzEpqtv3mDQ4CmO+u5fqszTWqHZt2V/OxMHdjzMAEwdHsXl/uU0lUp5mR4KTBOS0+DrXOvY9IjIMGA583uJwiIiki8hKETm/vYeIyC3WeenFxcU2FFu5w9b9FSRGBhMXHtzte4wfFOm4V74mOH2cy2ONxhnfVFPfyO6SasYN7FmCM25gJLtLqqmpb7SpZMqT3D3I+HLgTWNMy2Hqw4wxacCVwF9FZGRbFxpjnjHGpBlj0uLj491RVmWDrfkVjBsY2aN7xEcEExcepC04qiu6FWs0zvim7QWVGAPjBvUs1owbFIkxjvsp32dHgpMHDGnx9WDrWFsup1WTsTEmz/o3G/iSI/vMlQ+ra2wiq6iKsT1McESEsQMjtQVHaaxRbXJWfsYOjOjRfZyVsW0aa3oFOxKcNUCqiAwXkSAcgeV7MxREZAwQA6xocSxGRIKtz+OAucDW1tcq35RZWEVjs+lxrQocNavMwirqG3VF4z5MY41q07b8CiJDAkiKDu3RfQbHhBIREqCtxb1EjxMcY0wjcAfwEbANWGyM2SIiD4vIeS1OvRx43Ry5XetYIF1ENgBfAI+2nBGhfJuzxaWnXVTOe9Q3NbOruKrH91K+SWONas/W/ArGDYrs1lpbLYkI47S1uNfo8TRxAGPMUmBpq2MPtPr6oTau+xaYaEcZlPfZur+CsCB/hvXv1+N7HR5ovL+ix11eyndprFGtNTUbtudXcsXMobbcb9ygSF5fnUNTs+nylg/Ku+hKxspltuZXMHpAhC1BYnhcOCGBflqzUkodYU9pNYcamno8/sZp3MBIDjU0sae02pb7Kc/RBEe5hDGGbTbMoHLy9xNGD4jUvnGl1BGcMcGOsX4t76OxxvdpgqNcIvfgISprG20LOgDjBkawraCCI4dWKKX6sm35FQT6C6kJ9rTgpCZEEOAnOpOqF9AER7mEMziMGWBfgjMqMYKymgaKq+psu6dSyrdty69gZHw4QQH2/DkLCvBjeFw/dhbqhAZfpwmOconMIkdwGJUYbts9Ryc6amg7CzTwKKUcdhZWMSrRntYbp1EDIthZqIv9+TpNcJRLZBZWMigqxNbNMVOdCY4GHqUUUF3XSF7ZIVsrUgCjEiLIOVijWzb4OE1wlEvsLKwixeZaVVx4EDFhgZrgKKUAyLJailNsGn/jNHpAOMZ8d3/lmzTBUbZrajbsKq5iVIK9tSoRYVSiNh0rpRxc0RUOLVuLNcHxZZrgKNvlHKihrrGZVJuDDjgGGmcWVulMKqUUmYWVBPn7MTQ2zNb7DosNI8jfTytTPk4THGU7Z60q1eYuKnDU1CrrGskvr7X93kop37KzsJIR8f0I8Lf3T1mAvx8jE8I1wfFxmuAo2zmDQorNXVTA4dkSGniUUplFVS6pSIGjMrWzQOOML9MER9kuq6iKgVEhRNo4g8rJmeBkat+4Un1adV0juQcP2T7Wz2lUYgT7y2uprG1wyf2V62mCo2y3s7DSJa03ADH9gogLD2aHtuAo1aftKnZ2hbsuwQEdaOzLNMFRtmpqNmQV2b/wVkujB4STqQmOUn2aM/FwVRfV6MOtxRprfJUmOMpWuQcdM6jsnrbZUmpCBDsLq2hu1plUSvVVmUWOGVTDbJ5B5TQ4JpTQQH9twfFhmuAoWznHxti98FZLoxIjONTQRF7ZIZc9Qynl3TILq1wyg8rJz09I0ZlUPs2W3wwRmSciO0QkS0TubeP160WkWEQyrI+bW7x2nYhkWh/X2VEe5Tk7ixzBwFX94uDoogKdSdUXaaxRTjsLK13WPeWkC4v6th4nOCLiDzwFnAmMA64QkXFtnLrIGDPF+njWujYWeBCYBcwEHhSRmJ6WSXlOVmEVAyJdM4PKydk6pE3HfYvGGuVUU++YQZXqoskMTqmJ4RRV1lFeozOpfJEdLTgzgSxjTLYxph54HZjfyWvPAD4xxhwwxhwEPgHm2VAm5SE7iypd2noDEBUaSGJkMJlFWrPqYzTWKOC7PaJcOdav5f011vgmOxKcJCCnxde51rHWLhKRjSLypogM6eK1iMgtIpIuIunFxcU2FFvZrdmaQZXqwvE3Ts4tG1Sf4vJYo3HGN7hjrB9wOJZpa7Fvctcg4/eBZGPMJBw1pxe6egNjzDPGmDRjTFp8fLztBVQ9l3vwELUNrp1B5ZSSEE5Wkc6kUt/To1ijccY37LRmUCX3d80MKqekaOdMKm3B8UV2JDh5wJAWXw+2jh1mjCk1xtRZXz4LTO/stcp3OIOAqwf+gc6k6qM01ijAMdbPlTOonPz8hNTE8MNdYsq32PHbsQZIFZHhIhIEXA4saXmCiAxs8eV5wDbr84+A00Ukxhrwd7p1TPkg5yabrlrFuCVnK5HWrPoUjTUKcLTguCPOgHPdLY0zvqjHCY4xphG4A0ew2AYsNsZsEZGHReQ867SfiMgWEdkA/AS43rr2APBbHIFrDfCwdUz5oMzCSgZEhhAV6roZVE46k6rv0VijwDGDKufAIZeult6SzqTyXQF23MQYsxRY2urYAy0+vw+4r51rFwAL7CiH8izHzr7uqVXpTKq+SWON2lVUDeDyKeJOLWdSpSXHuuWZyh66krGyhXMGlbuajUFnUinVF2W6YTHRlnQmle/SBEfZIq/sEIcamtzWbAw6k0qpviizqIpAf2FY/35ueZ5zJpW2FvseTXCULZyzDNzVbAw6k0qpviizsIrhcf0IdPEMKifnTCptLfY9muAoWzhrN+7sonImUzrDQam+I8uNM6icUhLCtQXHB2mCo2yRWVhFXHgw0WFBbnumc72dTF2jQqk+obahiX0Haly+gnFroxIjKKyoo/yQzqTyJZrgKFtkFlW5tXsKvptJpS04SvUNu0uqaTbu7QqH756XqbHGp2iCo3rMGGsPKjfNamgpNUFnUinVVzhba90da0Zpa7FP0gRH9VhhRR1VdY1ur1UBh5dR15lUSvV+WYWV+AkMj3PPDCon3ZPKN2mCo3rsuwHG7u0XB51JpVRfkllURXL/fgQH+Lv1uX5+cnhZCuU7NMFRPebsIvJMF9V3q4wqpXq3TDcvJtpSamK4tuD4GE1wVI9lFlURExZI/37um0HlpKuMKtU31Dc2s6ek2iMVKXDEGp1J5Vs0wVE9llVUSWpCBCLi9mdHhQWSEKEzqZTq7faWVtPYbA5XatzNuSdVlrYW+wxNcFSPGGPYWVjFSA81G4NjHI72jSvVuznf457qonLOpNLWYt+hCY7qkZKqesoPNXhkBpWTcxl1nUmlVO+VWVSFCIyM90ysObwnlSY4PkMTHNUj7t7Zty2pCTqTSqneLrOoisExoYQGuXcGlZNzJpVOaPAdtiQ4IjJPRHaISJaI3NvG63eJyFYR2Sgin4nIsBavNYlIhvWxxI7yKPf5bpNNz/SLw3d94xp4ej+NNX1XZmGlR+MMOGZt6ng/39HjBEdE/IGngDOBccAVIjKu1WnrgTRjzCTgTeCxFq8dMsZMsT7O62l5lHtlFlYRERxAYmSwx8qgM6n6Bo01fVdjUzPZJdUe7QoHx/53OpPKd9jRgjMTyDLGZBtj6oHXgfktTzDGfGGMqbG+XAkMtuG5ygtkFlWSkhjukRlUTs6ZVNo33utprOmjcg4eor6x2WMDjJ10JpVvsSPBSQJyWnydax1rz03ABy2+DhGRdBFZKSLnt3eRiNxinZdeXFzcowIr+2QVeb5WBY4ZDtpF1eu5PNZonPFOzk0uUxM93UVl7UmllSmf4NZBxiJyNZAG/KnF4WHGmDTgSuCvIjKyrWuNMc8YY9KMMWnx8fFuKK06moPV9ZRU1Xm8VgU6k0odqbuxRuOMd3Jucjky3r17ULU2OCaUkEA/7Q73EXYkOHnAkBZfD7aOHUFETgXuB84zxtQ5jxtj8qx/s4Evgak2lEm5wQ6rVjXKw7Uq0JlUfYTGmj5qZ2ElSdGhRIQEerQcOpPKt9iR4KwBUkVkuIgEAZcDR8xQEJGpwL9xBJyiFsdjRCTY+jwOmAtstaFMyg2251cAMGZApIdLojOp+giNNX3U9vxKRg/wfEUKYFRChHZR+YgeJzjGmEbgDuAjYBuw2BizRUQeFhHnTIU/AeHAG62maI4F0kVkA/AF8KgxRoOOj9hRWEl0WKBHZ1A56Uyq3k9jTd9U39jMruIqxnhJgpOaGEFBRa3OpPIBAXbcxBizFFja6tgDLT4/tZ3rvgUm2lEG5X7bCyoZneiZPaha05lUfYPGmr4nu6SKxmbjNS04zkkVWUVVTB8W4+HSqI7oSsaqW5qbDTsLKr2mVgU6k0qp3mhHgeM97Q1d4fDdmMNMXfDP62mCo7ol9+AhquubGDPQO4IOODbhyyrSmVRK9Sbb8isJ9BdGeHgGlZPOpPIdmuCobtle4Bhg7C3NxuCoWdXU60wqpXqTHQUVjIwPJ9DfO/5c6Uwq3+EdvzHK5zibjb1hiriTzqRSqvfZ4WVd4aAzqXyFJjiqW7YXVDIkNpTwYFvGqdtCVxlVqncpr2lgf3kto71k/I1TSmI4BRW1VNTqTCpv5j1/nVSHDlTX815GHlv3VxAU4MeckXGcMT6RAA81224vqPCaQX9OzplUnuwbr6prZEnGfjJyDhLg78eM5BjOnDCQkEB/j5VJqa7IyCnjw80FFFbUkhQdyrmTB3msK9q5mOiYgd7XggOOypSnZlLtLKzk/Q37yTt4iITIEOZNGMCUIdEeKYu30gTHyxljeGXVPh79YDtVdY0kRARzqKGJV1btY8yACP5xxVS3789S29DE7pJqzpo40K3P7YzRAyLYZi1A6G5f7iji529spKSqjrjwIBqaDK+u2sefP9rJoxdN5LhUXfpfea/Sqjp+9e5mPthcQKC/kBARQmFFLU99mcV1xyRz/9lj3T4OZkeBczFR70pwnAnftvwKtyc4dY1NPLJ0Owu/3YO/n5AYEUxxVR3/+moX88YP4JELJxLTL8itZfJWmuB4saZmw0NLtvDSyr0cmxLHr84Zy5gBkTQ1Gz7aUsAD723hoqe/5eWbZzFpcLTbypVVVEWz8a4Bxk4TkqL4z9fZ1DU2ERzgvlaT9zLy+NmiDEYlRvDva6YzfVgMzc2Gb3eV8pv3t3DdgtX8Zv4Erpk9zG1lUqqz9pZWc92C1ewvr+Xu00Zx3dxkIkMCOVhdz98+y2Tht3vYXVLNf65NIyjAfUnOtoJKIkMCGBAZ4rZndsbgmFCiQgPZsr/crc+tbWjitpfX8sWOYq6fk8xPTkkltl8QlbUNvLhiL3/7NJP5Ty3n5ZtmMbR/mFvL5o10DI6XMsbwm/cdyc2tJ4zgxRtnHu4S8vcTzpo4kHd+NIfI0EBuXJju1plDm/Mcb+rxg6Lc9szOmjAoisZm49ZxOGv2HODuxRuYOTyWt26bc7hG5+cnHJsax7u3z+XkMQn8+t3NLFqzz23lUqozCitqueKZlZQfauC1H8zmx6ekEmnt+RTTL4iHzhvPHy6YyFc7i/nlO5swxn3LMGzJK2f8oCivWEy0JRFhQlIkm/Pc11psjOHX727mix3F/OGCiTx03nhirZaaiJBAbj8phddvnU1FbQNXPruS/HKdTaoJjpd69pvdvLhiL7ccP4L7zhyLn9/33+BDYsNYeMMM6hqa+NnrGTS5af2XTXnlRAQHMCzW+2oIE5IcSaAzCXO1A9X1/OiVdQyJDeOZa9Po18ag637BATx11TROGBXPL9/ZzLe7StxSNqWOpqa+kRsXrqHsUAMv3TSr3e6WK2cN5SenpPLm2lzeWf+9/U1doqGpmW0FlUwc7H0VKXBUpnYUVFLf2OyW572Rnssba3P58ckpXDlraJvnTBsaw0s3zqK8poGbX0intqHJLWXzVn0+wWluNjQ0Nbu1VnI0m3LLefTD7Zw5YQD3zhvT4bkpCRE8eN54Vu85wIJlu91Svs37KxifFNlm0uVpQ2PDiAgJYLObmo5/97+tlNXU88+rph2u9bYlOMCfp66aRnL/MH786nr2e9FaPcYY6hu96z3QGzU2NdPY5J4/hp316Afb2bK/gqeumsaEpI4TiZ+eksqM5BgefG+LW1oHMgurqG9sZvwg75rM4DQ+KYr6pma3LEtRVFHLb/+3lVnDY7nz1FEdnjtxcBR/vXwKW/ZXuL3F7Wicf2/dpU+OwdlfdojF6Tl8srWQnYWVNDQZokIDmTo0mvOnJHHOpIEem51U29DEXYsziAsP4tELJ3UqibhoWhJLN+Xz1093Mn/qIBIiXNdf3dDUzLb8Cq710rEkIsK4ge5pOv42q4S31+Vxx0kpjO3Eis7hwQE8c20a859czs8WZfDaD2Z7LEmsqG3gzfRcPticz8bccuoam+kX5M/4pCjmjR/ApTOGeNUSAL7IGMOyrBLeWpvL6t0H2F9ei4gjCT9hVDyXzxjKOA/+8V6WWcKLK/Zy49zhnDQ64ajn+/sJf75kMqc98TWPfbiDJy6b4tLyOVthJx4l8fKUCdb/3Zb9FS7vrn/4v1upa2zmkQsn4t+JmHHK2ER+ekoqf/ssk+NT4zl/apJLy9eR7QUVvLxyL8syS9hTWgPAgMgQjhnZn4umDWZuSn+XdUH2qQhWVdfIE5/s5KUVe2lobmZGciw3zB1ORHAA+8tr+SazmDsXZfD3zzP53fwJzEmJc3sZn/hkJ5lFVSy8YQZRYe23CLQkIvz6nHGc/sRXPP7RTv548SSXlc9Zq/LWZmNwDDR+eeVeGpuaXZaoNjcbfve/bQyJDeWOk1M6fd3I+HAeOHcc97y5kQXLd3PzcSNcUr72GGN4Y20ujyzdxsGaBsYPiuTKWUOJDQuitLqeldmlPPzfrfzts0zuPDWVa49J7lRAVUfakFPGb/+7lfS9B4kKDeT4UfFcEtcPYwzbCipZtCaHF1fs5YKpSTxwzji3z3qpqG3gnjc3MCK+H/fMG93p64b178cPjhvOU1/s4ppjhjFtqOtmEG3KKyc8OIDk/t6xRUNryf370S/Iny155ZA2xGXPWbfvIP/dmM9PT0llRHx4p6/7ySmpLMsq4dfvbWbWiFgGRoW6rIxtKa2q4w9Lt/PWulyCA/w4LjWecycPwk+E3SXVfLGjiHfW5zFlSDS/O3/CUVsQu6PPJDhr9x7kZ4syyD1Yw8XTB/Pjk1MZ0moMiTGGT7YW8sgH27nquVXcfmIKd502ym217PQ9B3jmm2yumDmUEztRo2ppeFw/rp+TzLPLdnPzccNdNnXc2fXjil9Gu0xIiqSusZldxdUum+m1dHM+W/MreOKyyV1e4+aS6YP5eEshj320g+NHxbttNeia+kb+782N/G9jPjOSY7j/7HFtrpuxIaeMP3+8g9+8v5UlG/bz5JXTSIp2b3D0VY1NzTz1xS7+/nkmsf2C+P0FE7h4+uDvzegrP9TAv7/axX++yWZldilPXjmV6cNi3VbO376/lYKKWt66bU6Xf39vOzGFxem5PPrBdhbfeoyLSuiINeMGeWdXODgmEYwfFMXm/a5tLX784x307xfELcd3rTLk7yf85dLJnPm3b/i/Nzby4o0z3fazzMgp49aX0jlQXc9tJ47kluNGfC+Jr2ts4q21eTzx6U7mP7WcO05K4SenpNpaoeoTY3BeW72PS/+9gmZjWHzrMTx28eTvJTfgaAk5ffwA/veTY7l42mCe/CKLOxdluGUQWU19I3e/sYGk6FDuP3tst+5x24kphAb68+QXWTaX7jub88rpF+TPcC+tVYFj8B/gsimcjU3N/OWTnYxKDOe8yV1v+hURHr1oIhHBAdy9eINb+qTLauq55F8rWLopn3vPHMOiW45pd1GwyUOiefHGmfzt8ilkFVZxzt+/YVmmDow+moraBm5YuIYnPt3JOZMG8tndJ3DVrGFtLlcQFRrIPfPG8PZtcwkK8OPK/6zik62Fbinnp1sLeWNtLj86MYWp3WiBCQ8O4EcnjmT17gOszC51QQkd77Ft+RVe2z3lND4pkq37K1w2wePbrBKWZ5Xyo5NS2pzAcDTD+vfj/rPHsiyrhFdWu2cG5ydbC7n03ysI9Pfj3dvn8ot5Y9psoQwO8OfKWUP59GcnMH/KIP72WaZjwHtNvW1lsSXBEZF5IrJDRLJE5N42Xg8WkUXW66tEJLnFa/dZx3eIyBl2lMepudnwyAfbuO/tTRyXGsfSnx5HWvLRa0lhQQE8dvEkfjFvDEs27OeWl9JdnuQ8+sF29pbW8OdLJnd77ENsvyCumT2M9zfsJ7vYNdOkN1nTNr21VgUwIj6c0EB/NrloJtXSzQVkF1dz12mjul3biAsP5nfnT2BTXjlPf7nL5hIeqaa+kRsWriGzsIrnrkvjhyeMPOr/n4gwf0oS790xl/iIYK57fjWL1+S4tJyd4a2xJq/sEJc8vYIVu0r540UT+dvlUzscdO40cXAUb982hzEDI7n1pXSWbNhvZ7G+52B1Pfe+vYkxAyL4ySmp3b7PFTOHEhcezD8+z7SxdN/JKq6itqH58KxIbzVhUBSHGppcFm//8XkWAyJDuKqdWVOdceXMoRyXGscjS7exzxoD4yordpVy+6vrGDsggiV3HNupsUlRYYE8fslk/nDBRFbsKuWip78l54A95exxgiMi/sBTwJnAOOAKERnX6rSbgIPGmBTgCeCP1rXjgMuB8cA84J/W/XqstqGJH7+2nn9/lc1Vs4by7LVpnQo4TiLCbSeO5A8XTOTLHcXcuWi9y2ZAtBzsN3tE/x7d6+bjRhAU4Mc/XfBHs76xma37K7y6ewocTbMTk6JYv6/MJfdfsGw3w+P6cfq4AT26z5kTB3Le5EH8/bNMl7U21Tc288OX17Ehp4y/XzGFk8ckdun6EfHhvP2jucxNieOetzby1093emxWhrfGmk255Zz/1HL2lx3ihRtnctmMrv0x6h8ezKs3zyItOZa7FmXw2TbXteT8+r3NlB+q5y+XTunRgn0hgf7cevwIlmeVsm7fQRtL6LAxx7sHGDtNtlpBXRFrtuVXsCK7lOvnJvdoqxcR4Y8XTcJfhJ+/uYFmF7U2bc4r5wcvpjM0NoyFN8w8vEZPZ8t45ayhvHTTTIor67jw6W9tWerDjhacmUCWMSbbGFMPvA7Mb3XOfOAF6/M3gVPEMWx6PvC6MabOGLMbyLLu12Nf7ihi6eZ87j9rLL87f0K3B5teOWsovzp7LEs3FXDf2/ZPuevuYL/2xEcEc2naEJZk7KeostaGEn5na34FdY3NHtt7pSumDYthy/5y29eBWL/vIBk5ZVx3zDBbWrEenj+emH5B3L14g+2thE3NhrsWZ/D1zmIeuXAi8yZ0b2uN8OAAnrsujYunD+bJz7M8udeXV8aaP328gyB/P9760RzmdnNiQj/rZzxuUCS3vbLOJWslvb9hP//dmM+dp46yZfbWlbOGEhkSwHMuWJ5irTU4e0Rc5wfVesKIuH5EhwWydq/9Sd7zy3cTEujH5TN6PoB5UHQoD5w7jtW7D7Dw2z09L1wr2cVVXLdgNVGhgbx008xuD5qfNaI/b902hyB/Px7+79Ye/721I8FJAlq2Xedax9o8xxjTCJQD/Tt5bbfMmzCQD396PD84fkSPp6DdfNwIfnpKKm+sdQyss5NzsN/jl3R9sGp7rp+TTH1TM6+stLfPdZ31Jp42LNrW+7rCtKHRNDQZ27upnl++h4jgAC62adZEdFgQj1wwke0FlbY29xtjeOC9zfx3Yz73nTmmy60KrQX6+/Gniyfx7u1zPblFh1fGmr9eNoV3bp/T48HiESGBvHDDTIbFhnHLi2ttXayyqKKWX7+3mclDorm1i4NV29MvOIArZg7lw80Ftq+kvm7fQaYNjfbqrnBwDDSeOiSatTa3YpVW1fFuxn4unDaY6DB7ZthdPH0wp4xJ4LGPttvapZZffohrnlsNwEs3zezxbK3UxAje/tEcnrxyao//dvvMIGMRuUVE0kUkvbi4uFPX2BmIHVNmh/Hvr7P591f2dP98uDm/R4P92jMiPpyTxyTwyqq9trZgrN13kKToULdPN+yOaVYr0zoba1YF5bUs3ZTPJWn2rhFz6rhELpo2mH9+uYsNOWW23POJT3byyqp93HrCCG49YaQt93QsT+/dXQY91Z04E9svyLa1p2L6BfHiTTOJCg3kugWr2V1S3eN7GmP4vzc3UtvQxOOXTLZ16YRr5yQD8OKKPbbds7ymgcwiz+3S3VXTh8WQVVRFeU2Dbfd8bfU+6hubucH6+dpBRHjkwokEB/jz8zc22DIw+mB1Pdc8t5ryQw28cOPMLk1j70hiZIgt7yk7ftPzgJbV2cHWsTbPEZEAIAoo7eS1ABhjnjHGpBlj0uLj3b8rs4jw0LnjOWfSQB75YDuL03s24LKoopb73t7ExKQofnpq9wf7tefGucMpqarnfRsHLa7be/Bw4uDt4sKDSe4fZmvT8csr99JkDNfbGHScHjh3HPHhwfz8jQ09TkoXLNvN3z/P4rK0IUddCdvHuDzWeDrOAAyMCuWlm2ZigGueW0VhRc+6ml9auZevdhZz/1ljSUmwt8snKTqUeeMH8NqqfVTXNdpyz3U5zpZi34g1hytTOfbEmoamZl5auZfjUuNsX+4jITKEh+ePZ92+Mp79JrtH96qqa+T6hWvYd6CGZ69L88rKjx0JzhogVUSGi0gQjoF8S1qdswS4zvr8YuBz4+hcWwJcbs18GA6kAqttKJNL+PkJf7l0CselxnHvWxu7Pa2zsamZuxZv4FBDE09cNoVAFyxGNzelP6MSw1mwfI8t44b2lx0iv7yW6UOje144N5k2NIZ1+8ps+f5rG5p4dfU+Th2b6JJdeqNCA/njxZPILKriL5/s7PZ93lqby8P/3cq88QP4/QUTvG6Twh7qM7FmRHw4C2+YwcHqeq59bnW3Wwe25Vfw+/9t48TR8VztotXHb5ibTEVtI2+vy7Xlfuv2HsTfT5g8ONqW+7na5MHR+Amst6kytXRTPoUVddw4d7gt92vtvMmDmDd+AI9/vJPtBd1bw6e2oYkfvuToRn3qymk9nhzjKj3+y2r1c98BfARsAxYbY7aIyMMicp512nNAfxHJAu4C7rWu3QIsBrYCHwK3G2O8enewoAA//nX1dCYOjub2V9exqhvrQPzpox0syyrhN+eNt71G5SQi3Dh3ONvyK1i1+0CP7+dsCXHnYmQ9NW1YDCVVdeyzYcrhkoz9HKiu54a5yT0vWDtOGBXP1bOH8szX2d2aLvy/jfn835sbmJvSn79ePsVj2424Sl+LNZMGR/PMtWnsLqnmxhfWcKi+a8U9WF3PLS+lEx0WyGMXT3JZsjt9WAyTBkfx/Ld7bJmhs3bvQcYOjOjWui+e0C84gLEDI0m3KcF5fvkeRsT144RRrmlBFBF+d8EEosICueXFtRyo7tq6M/WNzdz+yjqWZZXw2EWTOG1c12ZmupMtEdAYs9QYM8oYM9IY83vr2APGmCXW57XGmEuMMSnGmJnGmOwW1/7eum60MeYDO8rjav2CA3j++hkMiQnl5hfSuzTFd9Gaffz762yumT2sxwM/j+b8qUlEhwXy/PKez3JYkV1KeHAAYwd6bIBpl80a7kjGeroYmTGGBct3M2ZABMe4uKby63PGMSM5hv97Y0OXpt9+vKWAn76+nunDYvjPtWm2DVj3Nn0t1sxNieOvl09h3b6D3PbK2k4vClnb0MRtr6ylsLyOf1093aX704kIN8xNJru4mq8zOzduqT21DU2s3XuQGZ1Yr8ybzEiOZd2+gz3uXj48S3NOsksHWMeFB/PMNdMpqKjltpfXdrrc9Y3N3LloPZ9tL+J350/goumDXVZGO/SuKp4bxfYL4qWbZhEREsAVz6xkedbRp3W+uTaXe61FB399TuvlO+wXEujPFTOH8snWwh4vnLQ8q4TZI2J9qlUgJSGchIhglmX1LMFZmX2A7QWV3DA32eVdPsEB/vzr6ukkRoZw7XOrWbv36K1vL6/cyw9fXsv4pCgWXD+DsCDfqPmqzjlr4kB+f75jPa4bnl9z1O6qmvpGbnlpLat2H+BPl0yydQJDe86eOIj4iGCeX76nR/dZt/cgdY3NHOuBfQB74tiUOGobmnu8JpBzlqY7EoepQ2P408WTWL3nAD94Mf2oLYSOlbpXs3RTAb86e6zLujzt5Dt/rbzQoOhQFt16DAOjQrl2wWr+9mlmm2uZ1DY08cgH2/j5GxuYM7I//7k2rUeLbHXFNbOHISI9muWQc6CGvaU1zBnpW0FHRDg2JY5vs0p61HT+/PLdxIQFMn+Ke3bk7R8ezKJbZxMfEcyV/1nFa6v3tTmOqKymnp8tyuBX727mxNEJvPaDWUR0YTFL5TuunDWUP108iVW7SznvqWXttkruKq7i4qdX8E1mMX+8aJLbfmeDAvy4atZQvtpZTFZR96cgL99Vgr+fMHO4b7XgzB7ZH38/6VRFtz3OWZqXzrB3lmZH5k9J4rGLJrEsq4SLnv6WXe1MH1+VXcpZf/uGVdkH+Mulk92+SXB3aVWvh4bEhvHmbcdw/zubeeLTnSxOz+GKmUOYNjQGESEjp4xXV+8l58Ahrpw1lIfOHe+25AYcSdi8CQN4fU0Od546qlv92s5Fx7q7iJknzU2J4+31eWwrqOjUsuGt5Ryo4ZNthfzoxJFu7fYZGBXKGz88hjtfz+C+tzfx+up9XDpjCKMSI6iqa2R5ZgmL1uRQ09DEnaemcsdJKT7Vuqa67pK0IQyP68fPFmdw+TMrOXF0POdOGkRyXBilVfV8uq2Qd9bnERroz4LrZ3BSFzfs7amrZg3jn1/s4sUVe3h4/oRu3WNZVilThkT7XKIeHhzA1CHRLMss4f+6uQnISyv30GQM1x2TbGvZjuaStCH0Dw/irsUbmPfXr7lw6mBOGZtAbL8g9pbW8P7G/Xy5o5ghsaEsunW2T43D1ATHBhEhgfz9iqlcNH0wT32RxZ8/PnIWzPRhMfzhgokcl+qZaac3zk3mfxvzeXt9Htd0o1lxWVYpceHBjEr07lVF2+JMypZnlXQrwXl++R78RbhmdrLNJTu6uPBgXrxxJm+uzeWfX2Zx/zubD78W6C+cOjaRn56aypgB3r1fj7JPWnIsH995As9+k82LK/fy5Y7vxryEBflzSdoQfnbqKOIjgt1etviIYM6ZPJA31+Zy9+mjiQrtWpJSXtPAptwy7jgpxUUldK25KXH8/fNMymsaiArr2vde29DEq6tcN0vzaE4ek8jHdx7P3z7L5O11eSxqsQxKQkQw/3fGaK6fk+wzA7+dfKu0Xu6EUfGcMCqekqo6dhZU0mwc40AGRLlugF9nTBvqmOWwcPlurpo5tEuD1xqamvlyRxHzxg/wySnHA6JCGJUYzhfbi7nl+K4teFdZ28Di9BzOnjTQY/+Hfn7CpTOGcEnaYLJLqsk9eIiwIH/GDIjwuVquskdokD8/PiWV209KIbOoisKKWsJDAhg7IJLQIM8OLr9x7nDeXpfHG+k5Xe7G+GJHEc0GThrj3pYnuxyXGsffPsvkq8xizps8qEvXvr0uj4M1Ddx8rGumhndGQmQIv79gIr8+Zxxb8yuoONTgiJ8JEV6/onR7tE3bBeLCg5mTEsexqXEeT27gu1kOu4qr+aaLfcSrsg9QWdvo1VMBj+aM8QNYtbuU0qq6Ll23aE0OVXWN3OTBoOMkIoyMD+eEUfHMSI7V5Ebh5yeMHhDB8aPimTY0xuPJDcCEpChmJMew8Ns9XV4p9+OtBSREBPvM+jetTR0aQ1x4MB9uzu/Sdc3NjlmaE5IivWLsUUigP9OGxnDi6ATGDIj02eQGNMHpM86aOJC48OAuTxn/eGsBIYF+Hutes8MZ4wfQbODTLuzS3NjUzPPL9zAjOYZJPhpwlfKEG+YOJ/fgoS6932obmvhyRzGnjkv02T+o/n7C6eMT+WJ7cZemi3+V6RiYfdOxw32yldybaYLTRwQH+HP17KF8uaO43ZHyrTU2NfPh5gKOT433itphd40fFMmQ2FA+2FzQ6WuWWhsIekPrjVK+5PRxiSRFh3apMvXVzmJq6ps43YdbigHOnDCAQw1NfLWz8+sBPfNVNomRwZw9sWvdWuroNMHpQ66aNYzgAD/++UXnNgv9JquEoso6LpzmnqmmriIinDVxIMsySyiqPPq+Pk3Nhn98lklqQjinjRvghhIq1XsE+Ptx3ZxhrMw+QPqezq2i/ubaXOIjgn1u/ZvWZo/oT0xYIO+ub3NLxe9ZlV3KiuxSbjl+pFtn1/YV+hPtQ+Ijgrn2mGG8sz6XrKLKo57/ZnouMWGBnDzGt2tVAJemDaGx2fBG+tH3y1m6KZ/Moip+ckoq/j7aXK6UJ109exhx4cH86aMdR90LrqSqji+2F3Hh1CSfX+og0N+Pi6cP5pOthZ2qTP3100ziI4K5apZrV7Xvq3z7t0l12W0nphAa6H/UDR3zyw/x8dYCLpg6uFfULEbGh3PMiP68umpfh4Mf6xubeeKTnaQmhHP2xIFuLKFSvUdYUAB3nDSSVbsPsOwoExteXbWPxmbDJWnevex/Z10xcyiNzYbFa3I6PO/rncWsyC7lhye4d42tvsT3/3KpLontF8QPjh/B0k0FLMtsP/D85+vdNBtcurmku103Zxh5ZYdYsqH95uPnlu0mu6SaX5491mcHOyrlDa6YNZTBMaE8tGQLdY1tD7qtqW/k+eW7OXlMAikJvrPPXUdGxIdz/Kh4nl++h+q6xjbPqW9s5qH3t5DcP4yrZ2vrjatogtMH/fCEkQyP68cv39lETf3334B7S6t5edVe5k8ZxJBY9y865SqnjxvAuIGRPPFJZpuzHLKLq/j7Z5mcNi7R7avAKtXbBAf487vzJ7CruJqn2hn39++vsjlY08DtJ3VtjSpv97NTUymtrue5ZW0PtH7yiyyyi6t58NzxBAdo642raILTB4UE+vPIhRPJOVjDz9/YcMQ+TY1Nzdz39iYC/YR7zhjjwVLaz89PuO+sMew7UMOfP9pxxGuVtQ3c/up6QgL9eHj+eA+VUKne5cTRCVwwNYknP8/kix1FR7y2Lb+Cp7/axbmTB/nU8v+dMXVoDGdNHMCTn2exLb/iiNe+2lnMk59ncuG0JJ9d1NBXaILTR80e0Z/7zhzD0k0F3Lkog7KaeqrrGrnnzY18u6uUB88d7xWLFNrtuNR4rj1mGM8u281TX2TR2NTMvtIarnluNZmFlTxx2RQGRoV6uphK9Rq/O38CYwZEctvLa3l3fR7GGDbnlXPjwjXEhgXx63PGerqILvHb+ROICgvkxoVr2JxXTnOz4b2MPG59KZ1RiRH8tpv7danOk6ONcPdGaWlpJj093dPF8HnGGJ7+ahd/+mgH/iL4iVDf1Mzdp43ix6ekerp4LlPf2MzPFmfwv435hAT6UdvQTL8gfx6/dArzJui0cLuIyFpjTJqny9FdGmfsU1xZxy0vpbN+Xxmhgf4camgiISKY52+Y0a094nzFtvwKrnluNSVVdYQF+VNT38SUIdE8e10aceHu3y+st2ov1vQowRGRWGARkAzsAS41xhxsdc4U4GkgEmgCfm+MWWS9thA4ASi3Tr/eGJNxtOdq4LHX9oIKlmTsp7HZcOaEAUwdGuPpIrmcMYbPthWxfFcJ/fsFcdH0wdpyYzM7ExxPxBqNM/ZqbGrmf5vyWb+vjKToUC5JG0x0WJCni+Vy5TWOPe1yD9YwbVgMZ08c6PPT4b2NqxKcx4ADxphHReReIMYY84tW54wCjDEmU0QGAWuBscaYMivo/NcY82ZXnquBRynvZ3OC4/ZYo3FGKd/QXqzpaRo5H3jB+vwF4PzWJxhjdhpjMq3P9wNFgO9ubKSU8gSNNUqpLulpgpNojHFunVoAdLjkrYjMBIKAlnMGfy8iG0XkCRFpt1NSRG4RkXQRSS8u7vw+H0qpXsEtsUbjjFK9x1ETHBH5VEQ2t/Exv+V5xtHX1W5/l4gMBF4CbjDGNFuH7wPGADOAWOAX7VyOMeYZY0yaMSYtPl4rZUr1Nt4QazTOKNV7BBztBGPMqe29JiKFIjLQGJNvBZWids6LBP4H3G+MWdni3s4aWZ2IPA/8vEulV0r1GhprlFJ2OmqCcxRLgOuAR61/32t9gogEAe8AL7Ye4NciYAmOPvXNnXno2rVrS0RkbzfLHAd0vDmKe2g5jqTlOFJvKMcwG8vh9ljTwzijvJO3vK+6y5fL78qytxlrejqLqj+wGBgK7MUxdfOAiKQBPzTG3CwiVwPPA1taXHq9MSZDRD7HMQhQgAzrmqpuF6hzZU73hrU5tBxaDi1Hl8rhc7FGeR9v+X3uLl8uvyfK3qMWHGNMKXBKG8fTgZutz18GXm7n+pN78nylVN+gsUYp1VW62pBSSimlep2+mOA84+kCWLQcR9JyHEnLoZT9fP332ZfL7/ay++ReVEoppZRSHemLLThKKaWU6uU0wVFKKaVUr9NnEhwRuUREtohIszW11Hk8WUQOiUiG9fEvT5TDeu0+EckSkR0icoYry9HquQ+JSF6Ln8FZbnz2POv7zbI2UfQIEdkjIpus799tOyyKyAIRKRKRzS2OxYrIJyKSaf3r8u3d2ymHx34vlLKbt8Sa7hCR0S3ehxkiUiEid3q6XO1pK560eO1uETEiEufqcvSZBAfHwl4XAl+38douY8wU6+OHniiHiIwDLgfGA/OAf4qIv4vL0tITLX4GS93xQOv7ewo4ExgHXGH9HDzlJOv7d+daDQtx/H+3dC/wmTEmFfjM+toT5QAP/F4oZTcvjDVdYozZ4XwfAtOBGhyLWnqrhbQRT0RkCHA6sM8dhegzCY4xZpsxZocXl2M+8Loxps4YsxvIAma6t3RuNxPIMsZkG2Pqgddx/Bz6DGPM18CBVoePunO2m8qhVG/Rm2LNKTgq5V67ynYH8eQJ4B462EvOTn0mwTmK4SKyXkS+EpHjPFSGJCCnxde51jF3uUMcOy0vcEeXiMXT33NLBvhYRNaKyC0eKoNTl3bOdjFP/F4oZTdvijU9dTnwmqcL0VXWprl5xpgN7npmT/ei8ioi8ikwoI2X7jfGfG/vGks+MNQYUyoi04F3RWS8MabCzeVwqY7KBDwN/BbHH/nfAo8DN7qvdF7hWGNMnogkAJ+IyHarFuJRxhgjIp5ay0F/L5TyItZ+a+cB93m6LF0hImHAL3F0T7lNr0pwOtqNuINr6oA66/O1IrILGAV0e6Bpd8oB5AFDWnw92Dpmi86WSUT+A/zXrucehUu/564wxuRZ/xaJyDs4mrQ9leB0audsVzPGFDo/d/PvhVJ285pY00NnAutavjd9xEhgOLDBsd8tg4F1IjLTGFPgqof2+S4qEYl3DuYVkRFAKpDtgaIsAS4XkWARGW6VY7U7Hmz9EXW6gE7u6m6DNUCqiAy3aiaX4/g5uJWI9BORCOfnOGoZ7voZtMW5cza0s3O2O3jw90Ipu3lFrLHBFfhg95QxZpMxJsEYk2yMScbRRTjNlckN9LIWnI6IyAXAP3DsKPw/EckwxpwBHA88LCINQDOOXYZdNtiyvXIYY7aIyGJgK9AI3G6MaXJVOVp5TESm4OiK2APc6o6HGmMaReQO4CPAH1hgjNlylMtcIRF4x6pZBACvGmM+dMeDReQ14EQgTkRygQeBR4HFInIT1s7ZHirHiZ74vVDKbl4Ua7rNqnydhg+8D9uKJ8aY59xeDt2qQSmllFK9TZ/volJKKaVU76MJjlJKKaV6HU1wlFJKKdXraIKjlFJKqV5HExyllFJK9Tqa4CillFKq19EERymllFK9zv8DmephZgg9IOsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "\n",
    "x1 = np.arange(-np.pi/2, np.pi/2+0.001,  0.001)\n",
    "y1 = np.sinc(np.pi*x1)\n",
    "fig, axs = plt.subplots(2, 2, figsize=(8, 5), layout=\"tight\")\n",
    "for n, ax in enumerate(axs.flat):\n",
    "    ax.plot(x1*10., y1)\n",
    "\n",
    "locator = ticker.AutoLocator()\n",
    "axs[0, 0].xaxis.set_major_locator(locator)\n",
    "axs[0, 0].set_title(\"AutoLocator\")\n",
    "\n",
    "locator = ticker.MaxNLocator(nbins=10)\n",
    "axs[0, 1].xaxis.set_major_locator(locator)\n",
    "axs[0, 1].set_title(\"MaxNLocator\")\n",
    "\n",
    "locator = ticker.MultipleLocator(5)\n",
    "axs[1, 0].xaxis.set_major_locator(locator)\n",
    "axs[1, 0].set_title(\"MultipleLocator\")\n",
    "\n",
    "locator = ticker.FixedLocator([0, 7, 14, 21, 28])\n",
    "axs[1, 1].xaxis.set_major_locator(locator)\n",
    "axs[1, 1].set_title(\"FixedLocator\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "此外`matplotlib.dates` 模块还提供了特殊的设置**日期型**刻度格式和位置的方式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T13:07:22.706411Z",
     "iopub.status.busy": "2021-11-25T13:07:22.706072Z",
     "iopub.status.idle": "2021-11-25T13:07:22.956863Z",
     "shell.execute_reply": "2021-11-25T13:07:22.955997Z",
     "shell.execute_reply.started": "2021-11-25T13:07:22.706382Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import datetime\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 特殊的日期型locator和formatter\n",
    "locator = mdates.DayLocator(bymonthday=[1, 15, 25])\n",
    "formatter = mdates.DateFormatter('%b %d')\n",
    "\n",
    "x1 = np.arange(-np.pi/4, np.pi/4+0.05, 0.05)\n",
    "y1 = np.sinc(np.pi*x1)\n",
    "fig, ax = plt.subplots(layout=\"tight\")\n",
    "ax.xaxis.set_major_locator(locator)\n",
    "ax.xaxis.set_major_formatter(formatter)\n",
    "base = datetime.datetime(2021, 11, 25, 21, 7, 0)\n",
    "time = [base + datetime.timedelta(days=x) for x in range(len(x1))]\n",
    "ax.plot(time, y1)\n",
    "ax.tick_params(axis='x', rotation=70)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. 其他进阶案例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T13:27:22.480991Z",
     "iopub.status.busy": "2021-11-25T13:27:22.480023Z",
     "iopub.status.idle": "2021-11-25T13:27:22.591474Z",
     "shell.execute_reply": "2021-11-25T13:27:22.590785Z",
     "shell.execute_reply.started": "2021-11-25T13:27:22.480956Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#这个案例中展示了如何进行坐标轴的移动，如何更改刻度值的样式\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "x = np.linspace(-3, 3, 50)\n",
    "y1 = 2 * x + 1\n",
    "y2 = x ** 2\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(x, y2, color=\"deepskyblue\")\n",
    "ax.plot(x,y1,color='orange', linewidth=1.0,linestyle = '--')\n",
    "\n",
    "ax.set_xticks(ticks=np.linspace(-3,5,5))\n",
    "ax.set_yticks(ticks=[-2, 0, 2, 5], labels=[r'one', r'$\\alpha$', r'three', r'four'])\n",
    "ax.set_xlim((-3,5))\n",
    "ax.set_ylim((-3,5))\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('y')\n",
    "\n",
    "# gca = 'get current axes' 获取现在的 axes\n",
    "# fig=plt.gcf是获取当前的figure，其中gcf代表的是get current figure\n",
    "ax = plt.gca()\n",
    "'''\n",
    "许多函数都是对当前的Figure或Axes对象进行处理，如\n",
    "def plt.plot(*args, scalex=True, scaley=True, data=None, **kwargs):\n",
    "    return gca().plot(\n",
    "        *args, scalex=scalex, scaley=scaley,\n",
    "        **({\"data\": data} if data is not None else {}), **kwargs)\n",
    "先会通过plt.gca()获得当前的Axes对象ax，然后再调用ax.plot()方法实现真正的绘图。\n",
    "'''\n",
    "\n",
    "# 通过ax.spines方法获得当前ax的顶部和右边的轴，设置为不可见\n",
    "# 然后将ax左边轴和底部轴的位置\n",
    "# 最后set_ticks_position()方法设置ticks在x轴或y轴的位置\n",
    "ax.spines[[\"top\", \"right\"]].set_visible(False)\n",
    "ax.spines[[\"left\", \"bottom\"]].set_position(('data',0))\n",
    "\n",
    "# 因为x轴或y轴的默认值是bottom和left是ticks在，所以下面两行代码也可以不写\n",
    "# ax.xaxis.set_ticks_position('bottom')\n",
    "# ax.yaxis.set_ticks_position('left')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 三、[legend（图例）](https://matplotlib.org/stable/tutorials/intermediate/legend_guide.html)\n",
    "\n",
    "图例的设置会使用一些常见术语：\n",
    "\n",
    "1. legend entry（图例条目）\n",
    "\n",
    "   图例有一个或多个 legend entries 组成。一个 entry 由一个 key 和一个 label 组成。\n",
    "\n",
    "2. legend key（图例键）\n",
    "\n",
    "   每个 legend label 左面的 colored/patterned marker（彩色/图案标记）\n",
    "\n",
    "3. legend label（图例标签）\n",
    "\n",
    "   描述由 key 来表示的 handle 的文本\n",
    "\n",
    "4. legend handle（图例句柄）\n",
    "\n",
    "   用于在图例中生成适当图例条目的原始对象"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T13:42:17.399186Z",
     "iopub.status.busy": "2021-11-25T13:42:17.398531Z",
     "iopub.status.idle": "2021-11-25T13:42:17.524084Z",
     "shell.execute_reply": "2021-11-25T13:42:17.523481Z",
     "shell.execute_reply.started": "2021-11-25T13:42:17.399151Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 以下面这个图为例\n",
    "# - 右侧的方框中的共有两个 legend entry；\n",
    "# - 两个 legend key，分别是一个蓝色和一个橙色的 legend key；\n",
    "# - 两个 legend label，一个名为 'Line Up' 和一个名为 'Line Down' 的legend label；\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "red_patch = mpatches.Patch(color='deepskyblue', label='Line Up')\n",
    "orange_patch = mpatches.Patch(color='orange', label='Line Down')\n",
    "ax.legend(handles=[red_patch, orange_patch])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "Axes.legend(*args, **kwargs) -> matplotlib.legend.Legend\n",
    "\n",
    "# 常用以下三种形式\n",
    "legend()\n",
    "legend(handles, labels)\n",
    "legend(handles=handles)\n",
    "legend(labels)\n",
    "```\n",
    "参数：\n",
    "- handles: sequence of Artist, optional\n",
    "- labels: list of str, optional\n",
    "- loc: str or pair of floats, 图例位置，default: 'best'\n",
    "\n",
    "  `{0: 'best', 1: 'upper right', 2: 'upper left', 3: 'lower left', 4: 'lower right', 5: 'right', 6: 'center left', 7: 'center right', 8: 'lower center', 9: 'upper center', 10: 'cente}`\n",
    "\n",
    "- bbox_to_anchor: BboxBase, 2-tuple, or 4-tuple of floats, 用于结合loc定位图例的框\n",
    "\n",
    "- ncol: int, 图例列数, default: 1\n",
    "- prop: None or matplotlib.font_manager.FontProperties or dict, 图例字体配置\n",
    "- fontsize: int or {'xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'}, 图例字体大小\n",
    "- labelcolor: str or list, 图例标签颜色, default: 'None'\n",
    "- frameon: bool, 图例背景, default: True\n",
    "\n",
    "<br/>\n",
    "\n",
    "更多详细信息请参看：[Axes.legend](https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.legend.html#matplotlib.axes.Axes.legend), [Legend](https://matplotlib.org/stable/api/legend_api.html#matplotlib.legend.Legend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T14:33:07.700050Z",
     "iopub.status.busy": "2021-11-25T14:33:07.699318Z",
     "iopub.status.idle": "2021-11-25T14:33:08.612222Z",
     "shell.execute_reply": "2021-11-25T14:33:08.611549Z",
     "shell.execute_reply.started": "2021-11-25T14:33:07.700020Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "red_patch = mpatches.Patch(color='deepskyblue', label='Line Up')\n",
    "orange_patch = mpatches.Patch(color='orange', label='Line Down')\n",
    "\n",
    "fig = plt.figure(figsize=(12, 12))\n",
    "ax1 = fig.add_subplot(331)\n",
    "ax1.legend(handles=[red_patch, orange_patch])\n",
    "\n",
    "ax2 = fig.add_subplot(332)\n",
    "ax2.legend(handles=[red_patch, orange_patch], labels=[\"a\", \"b\"])\n",
    "\n",
    "ax3 = fig.add_subplot(333)\n",
    "ax3.legend(handles=[red_patch, orange_patch], loc=(0.1, 0.1))\n",
    "\n",
    "ax4 = fig.add_subplot(334)\n",
    "# 将图例放在axes右下象限的最佳位置\n",
    "# ax4.legend(handles=[red_patch, orange_patch], loc=\"best\", bbox_to_anchor=(0.5, 0., 0.5, 0.5))\n",
    "# 要将图例的右上角放在axes的中心\n",
    "ax4.legend(handles=[red_patch, orange_patch], loc='upper right', bbox_to_anchor=(0.5, 0.5))\n",
    "\n",
    "ax5 = fig.add_subplot(335)\n",
    "ax5.legend(handles=[red_patch, orange_patch], ncol=2)\n",
    "\n",
    "ax6 = fig.add_subplot(336)\n",
    "ax6.legend(handles=[red_patch, orange_patch], prop=dict(weight=\"bold\", size=12))\n",
    "\n",
    "ax7 = fig.add_subplot(337)\n",
    "ax7.legend(handles=[red_patch, orange_patch], edgecolor=\"green\")\n",
    "\n",
    "ax8 = fig.add_subplot(338)\n",
    "ax8.legend(handles=[red_patch, orange_patch], facecolor=plt.cm.Oranges(0.12))\n",
    "\n",
    "ax9 = fig.add_subplot(339)\n",
    "rng1 = np.random.RandomState(23857)\n",
    "rng2 = np.random.RandomState(23856)\n",
    "line1, = ax9.plot(range(10), rng1.randn(10), label=\"a\", marker=\".\", ls=\"-.\")\n",
    "line2, = ax9.plot(range(10), rng2.randn(10), label=\"b\", marker=\"2\", ls=\"--\")\n",
    "ax9.legend(handles=[line1, line2], numpoints=3)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 四、总结\n",
    "\n",
    "重点学习了 xlabel、xticks、legend。\n",
    "其中xticks可以使用 Locator 和 Formatter 实现更加灵活的设置。\n",
    "😄"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 五、参考\n",
    "\n",
    "1. [fantastic-matplotlib 第四回：文字图例尽眉目](https://gitee.com/datawhalechina/fantastic-matplotlib/blob/main/%E7%AC%AC%E5%9B%9B%E5%9B%9E%EF%BC%9A%E6%96%87%E5%AD%97%E5%9B%BE%E4%BE%8B%E5%B0%BD%E7%9C%89%E7%9B%AE.ipynb)\n",
    "2. [Text in Matplotlib Plots](https://matplotlib.org/stable/tutorials/text/text_intro.html)\n",
    "3. [Legend guide](https://matplotlib.org/stable/tutorials/intermediate/legend_guide.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 六、作业\n",
    "\n",
    "### 1. 尝试在一张图中运用所讲过的功能，对title、text、xlable、ylabel、数学表达式、tick and ticklabel、legend进行详细的设计.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-25T15:26:51.305042Z",
     "iopub.status.busy": "2021-11-25T15:26:51.304528Z",
     "iopub.status.idle": "2021-11-25T15:26:51.497866Z",
     "shell.execute_reply": "2021-11-25T15:26:51.497271Z",
     "shell.execute_reply.started": "2021-11-25T15:26:51.305008Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import sys\n",
    "sys.path.append(\"external-libraries\")\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotlib.font_manager as font_manager\n",
    "import matplotlib.ticker as ticker\n",
    "\n",
    "font_props = font_manager.FontProperties(fname=\"data/data118028/TIMES.TTF\")\n",
    "\n",
    "x = np.arange(-5, 5.01, 0.1)\n",
    "y = np.exp(-0.5*x**2)\n",
    "\n",
    "fig = plt.figure(layout=\"tight\")\n",
    "fig.suptitle(\"Title\", fontsize=25, ha=\"center\")\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_title(\"Math Cure\", fontsize=18)\n",
    "ax.set_xlabel(\"x\", family=font_props.get_family(), fontsize=15)\n",
    "ax.set_ylabel(\"y\", fontsize=15)\n",
    "major_formatter = ticker.StrMethodFormatter(\"{x:1.1f}\")\n",
    "ax.xaxis.set_major_formatter(major_formatter)\n",
    "minior_formatter = ticker.StrMethodFormatter(\"{x:1.1f}\")\n",
    "ax.xaxis.set_minor_formatter(minior_formatter)\n",
    "major_loacator = ticker.MultipleLocator(base=1)\n",
    "ax.xaxis.set_major_locator(major_loacator)\n",
    "ax.text(x=0.26, y=0.6, s=r\"$e^{-\\frac{x^2}{2}}$\", fontsize=22, transform=ax.transAxes)\n",
    "\n",
    "line, = ax.plot(x, y)\n",
    "line.set_color(\"deepskyblue\")\n",
    "line.set_linestyle(\"--\")\n",
    "\n",
    "leg = ax.legend(handles=[line], labels=[\"Line\"], edgecolor=\"steelblue\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 阅读你可能用到文献或者相关书籍，思考自己如何才能通过学过的例子将自己认为比较好看的图给复现出来."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-26T03:10:32.829010Z",
     "iopub.status.busy": "2021-11-26T03:10:32.827965Z",
     "iopub.status.idle": "2021-11-26T03:10:34.844885Z",
     "shell.execute_reply": "2021-11-26T03:10:34.844135Z",
     "shell.execute_reply.started": "2021-11-26T03:10:32.828961Z"
    }
   },
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "fmri = sns.load_dataset(\"fmri\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-26T03:10:43.925673Z",
     "iopub.status.busy": "2021-11-26T03:10:43.924755Z",
     "iopub.status.idle": "2021-11-26T03:10:43.943974Z",
     "shell.execute_reply": "2021-11-26T03:10:43.943351Z",
     "shell.execute_reply.started": "2021-11-26T03:10:43.925627Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>subject</th>\n",
       "      <th>timepoint</th>\n",
       "      <th>event</th>\n",
       "      <th>region</th>\n",
       "      <th>signal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>s13</td>\n",
       "      <td>18</td>\n",
       "      <td>stim</td>\n",
       "      <td>parietal</td>\n",
       "      <td>-0.017552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>s5</td>\n",
       "      <td>14</td>\n",
       "      <td>stim</td>\n",
       "      <td>parietal</td>\n",
       "      <td>-0.080883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>s12</td>\n",
       "      <td>18</td>\n",
       "      <td>stim</td>\n",
       "      <td>parietal</td>\n",
       "      <td>-0.081033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>s11</td>\n",
       "      <td>18</td>\n",
       "      <td>stim</td>\n",
       "      <td>parietal</td>\n",
       "      <td>-0.046134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>s10</td>\n",
       "      <td>18</td>\n",
       "      <td>stim</td>\n",
       "      <td>parietal</td>\n",
       "      <td>-0.037970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1059</th>\n",
       "      <td>s0</td>\n",
       "      <td>8</td>\n",
       "      <td>cue</td>\n",
       "      <td>frontal</td>\n",
       "      <td>0.018165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1060</th>\n",
       "      <td>s13</td>\n",
       "      <td>7</td>\n",
       "      <td>cue</td>\n",
       "      <td>frontal</td>\n",
       "      <td>-0.029130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1061</th>\n",
       "      <td>s12</td>\n",
       "      <td>7</td>\n",
       "      <td>cue</td>\n",
       "      <td>frontal</td>\n",
       "      <td>-0.004939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1062</th>\n",
       "      <td>s11</td>\n",
       "      <td>7</td>\n",
       "      <td>cue</td>\n",
       "      <td>frontal</td>\n",
       "      <td>-0.025367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1063</th>\n",
       "      <td>s0</td>\n",
       "      <td>0</td>\n",
       "      <td>cue</td>\n",
       "      <td>parietal</td>\n",
       "      <td>-0.006899</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1064 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     subject  timepoint event    region    signal\n",
       "0        s13         18  stim  parietal -0.017552\n",
       "1         s5         14  stim  parietal -0.080883\n",
       "2        s12         18  stim  parietal -0.081033\n",
       "3        s11         18  stim  parietal -0.046134\n",
       "4        s10         18  stim  parietal -0.037970\n",
       "...      ...        ...   ...       ...       ...\n",
       "1059      s0          8   cue   frontal  0.018165\n",
       "1060     s13          7   cue   frontal -0.029130\n",
       "1061     s12          7   cue   frontal -0.004939\n",
       "1062     s11          7   cue   frontal -0.025367\n",
       "1063      s0          0   cue  parietal -0.006899\n",
       "\n",
       "[1064 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fmri"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-26T03:33:00.106464Z",
     "iopub.status.busy": "2021-11-26T03:33:00.105611Z",
     "iopub.status.idle": "2021-11-26T03:33:00.119931Z",
     "shell.execute_reply": "2021-11-26T03:33:00.119271Z",
     "shell.execute_reply.started": "2021-11-26T03:33:00.106426Z"
    }
   },
   "outputs": [],
   "source": [
    " parietal = fmri.loc[fmri.loc[:, \"region\"] == \"parietal\", [\"timepoint\", \"signal\"]]\r\n",
    " parietal = parietal.sort_values(by=[\"timepoint\"]).reset_index().drop(\"index\", axis=1)\r\n",
    " parietal = parietal.groupby(\"timepoint\").agg([\"mean\", \"max\", np.std])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-26T03:33:51.419842Z",
     "iopub.status.busy": "2021-11-26T03:33:51.418757Z",
     "iopub.status.idle": "2021-11-26T03:33:51.431886Z",
     "shell.execute_reply": "2021-11-26T03:33:51.431190Z",
     "shell.execute_reply.started": "2021-11-26T03:33:51.419803Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">signal</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>max</th>\n",
       "      <th>min</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timepoint</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <td>0.029822</td>\n",
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       "    <tr>\n",
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       "      <td>0.041580</td>\n",
       "      <td>0.185581</td>\n",
       "      <td>-0.089708</td>\n",
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       "    <tr>\n",
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       "      <td>0.346775</td>\n",
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       "      <td>0.476055</td>\n",
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       "      <td>0.564985</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.106658</td>\n",
       "      <td>0.494787</td>\n",
       "      <td>-0.108222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.036947</td>\n",
       "      <td>0.337143</td>\n",
       "      <td>-0.181241</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.019913</td>\n",
       "      <td>0.221716</td>\n",
       "      <td>-0.152929</td>\n",
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       "    <tr>\n",
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       "      <td>0.089231</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>-0.067962</td>\n",
       "      <td>0.009137</td>\n",
       "      <td>-0.238474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>-0.066543</td>\n",
       "      <td>0.030923</td>\n",
       "      <td>-0.255486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>-0.057938</td>\n",
       "      <td>0.039476</td>\n",
       "      <td>-0.224351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-0.046433</td>\n",
       "      <td>0.041342</td>\n",
       "      <td>-0.169312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-0.036852</td>\n",
       "      <td>0.037435</td>\n",
       "      <td>-0.134828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-0.032701</td>\n",
       "      <td>0.029307</td>\n",
       "      <td>-0.131641</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>-0.031997</td>\n",
       "      <td>0.031867</td>\n",
       "      <td>-0.121574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-0.033452</td>\n",
       "      <td>0.043195</td>\n",
       "      <td>-0.103513</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             signal                    \n",
       "               mean       max       min\n",
       "timepoint                              \n",
       "0         -0.024080  0.052619 -0.064454\n",
       "1         -0.034378  0.029822 -0.082174\n",
       "2         -0.017773  0.077277 -0.110565\n",
       "3          0.041580  0.185581 -0.089708\n",
       "4          0.119216  0.346775 -0.046347\n",
       "5          0.168279  0.476055 -0.008158\n",
       "6          0.161232  0.564985 -0.046841\n",
       "7          0.106658  0.494787 -0.108222\n",
       "8          0.036947  0.337143 -0.181241\n",
       "9         -0.019913  0.221716 -0.152929\n",
       "10        -0.054041  0.089231 -0.176453\n",
       "11        -0.067962  0.009137 -0.238474\n",
       "12        -0.066543  0.030923 -0.255486\n",
       "13        -0.057938  0.039476 -0.224351\n",
       "14        -0.046433  0.041342 -0.169312\n",
       "15        -0.036852  0.037435 -0.134828\n",
       "16        -0.032701  0.029307 -0.131641\n",
       "17        -0.031997  0.031867 -0.121574\n",
       "18        -0.033452  0.043195 -0.103513"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parietal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-26T03:35:29.582892Z",
     "iopub.status.busy": "2021-11-26T03:35:29.581822Z",
     "iopub.status.idle": "2021-11-26T03:35:29.587386Z",
     "shell.execute_reply": "2021-11-26T03:35:29.586603Z",
     "shell.execute_reply.started": "2021-11-26T03:35:29.582849Z"
    }
   },
   "outputs": [],
   "source": [
    "parietal.columns = [\"mean\", \"max\", \"min\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-26T03:35:58.856267Z",
     "iopub.status.busy": "2021-11-26T03:35:58.855242Z",
     "iopub.status.idle": "2021-11-26T03:35:58.861287Z",
     "shell.execute_reply": "2021-11-26T03:35:58.860544Z",
     "shell.execute_reply.started": "2021-11-26T03:35:58.856228Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "       17, 18])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-26T03:36:34.673031Z",
     "iopub.status.busy": "2021-11-26T03:36:34.671953Z",
     "iopub.status.idle": "2021-11-26T03:36:34.804807Z",
     "shell.execute_reply": "2021-11-26T03:36:34.804196Z",
     "shell.execute_reply.started": "2021-11-26T03:36:34.672993Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f06957f7e10>]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\r\n",
    "import numpy as np\r\n",
    "import matplotlib.pyplot as plt\r\n",
    "\r\n",
    "# plt.scatter(fmri.loc[fmri.loc[:, \"region\"] == \"parietal\", \"timepoint\"].values, fmri.loc[fmri.loc[:, \"region\"] == \"parietal\", \"signal\"].values)\r\n",
    "plt.plot(parietal.index.to_numpy(), parietal.loc[:, \"mean\"].to_numpy())\r\n",
    "plt.plot(parietal.index.to_numpy(), parietal.loc[:, \"max\"].to_numpy())\r\n",
    "plt.plot(parietal.index.to_numpy(), parietal.loc[:, \"min\"].to_numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-26T03:11:02.395917Z",
     "iopub.status.busy": "2021-11-26T03:11:02.394835Z",
     "iopub.status.idle": "2021-11-26T03:11:03.393449Z",
     "shell.execute_reply": "2021-11-26T03:11:03.392710Z",
     "shell.execute_reply.started": "2021-11-26T03:11:02.395877Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f06a49b8450>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0FP2mL2HCRNLihQ9rWDIpl2mFPdU7B8uskiyuXzKRV3bVs7mqtd/7ux06gaip2sIqhp3Vq1fj8dgPJxs3buSWW24BYM6cOUyZMuW40Vi5ciU5OTm43W7mzZtHVVVVyuM9+OCDLFq0iHPPPZcjR45QUTHywt9qpaHoF5kIE76+t4HWcIKvXTEx7ZjBctPyybx/qJmfrq/goTX9z6YydEFDIMo0l3+YZqgYdXpZEYwUqSTPU+FyndBs03Ud0+z5QPP666/z6quv8s477+D1ernkkku6yauPFGqloegXbeEE4XgStyO1zpQlJX/YUs20Qh+LJuYM2zychsZXLp9FSyjOYwPIpvI7DapbI1jW6SXYqRi7XHjhhcdly/ft28fhw4eZPXt2r/s4HA4SiQQA7e3t5OXl4fV62bNnD+++++6wzzkVymgo+sWhPoQJN1e1cqQ1wvVLJmRc8DdQjrmpXt5Vz+bD/XNTGbpGwpK0RxLDNDuFojt33nknlmWxYMECPvWpT7F27dpuK4xU3H777SxcuJCbb76ZVatWYZomc+fO5d577+Xcc88doZl3R0mjKzKmI5pgU2VLr8KE3/rDdmrbI/zi1qXHZUCGk7hp8eWntxBNWDy0Zkm/3FTBmEm2x6B8/PCtiBQjy1iQRj8VUNLoihHhSEsYl5F+lVFRH2B7dTurF40fEYMBnW6qlbNoCcV4vJ9uKp9TpyEQI2Ymh2l2CsXphzIaiowIx00aOmK9qsz+YWs1XqfOVeWlIzgzmF2axfVLJvCXfrqphBAIoCWo+mwoFJmijIYiI6pbIxiaSBunqO+I8tb+JlaVl46K9PhNy6cwMc/DT1/bTzieeSqt32VwtDXM6eamVSiGC2U0FH0STSSpbouQ7UlfzPf8thqEEKxeNH4EZ3YCp6Hx5ZVltIRiPPZWZcb7uQydYMwkqGo2FIqMUEZD0Sf17VEEpBUmDEZNXt5Vx8VlRRSMYo/wOaXZfGzxBP6ys44t/XBTOXSdhg4lK6JQZIIyGopeSSQtDreGyfGklxI/JhnysSUTRnBmqbnpnMlMyPXw0/WZu6n8LoPa9ghJVbOhUPSJMhqKXmnsiJG00gsTHpMMOWtyaskQkYyhJUKIZAys4c9Schk6X7m8jOZgjMczdFPpmsC0JG1hFRBXjG2ee+45du3aNapzUDIiirQkLUllS+/ChMclQ5akkAyxTDwNm9HMGBIQAEJgaQ6k7kTqbizdidRdSM2F1A0QBlLTkZoB4tif/Xu2mVOazUcXT+APW6pZMbOQxZNy+9zH49CpbouMqntNoeiL5557jmuvvZZ58+aN2hzUSkORluZgjLiZXpjwmGTI9DSSIY5gNZoZw/Tkk/TkY3ryMV25WIYbkIhEECPShDNwGFfbHjxNO3A3bsVbvwlf7Xv4at7Gd/QNvDXvIsxIv+Z+c6eb6sHXKjJyU3kcOs3BONGEqtlQDI5f//rXLF++nMWLF3PHHXfw8MMPc8899xzfvnbtWu66666UY5NJ+/vn9/v59re/fVycsL6+nrfffpvnn3+ee+65h8WLF3PgwIFRuT5lNBRpOdIawetIvxjd1ItkiDCjuNorMV0nGRMhQDPs1YXDi+X0k3TlkHTndzcunnzirnxijjwSZhxnW/9+IC5D5ysry2gKxFj7dmWf44UQCAFNQRUQVwyc3bt38/TTT/PWW2+xdetWdF3H7/fzhz/84fiYp59+mhtvvDHl2GPaVKFQiHPPPZdt27Zx0UUX8Ytf/ILzzz+f1atXc//997N161ZmzJgxKteo3FOKlEQTSToiCQp7cdf8YUs1hX4XF8ws7LHN2VGFFAK07hXkUtpur6QlsSxJUkosKZGAJuztx8LRhiZw6hqmIwvRVo3uH0/SnZ/xNcwZZ7upnttazYoZhSzqw02V5XJwtDXChFzPsOtmKU5P/vrXv7Jp0yaWLVsGQCQSobi4mOnTp/Puu+9SVlbGnj17WLFiBQ8//HDKsQBOp5Nrr70WgLPPPptXXnlldC4oBcpoKFLSEUnQ233zmGTI51ZM6yEZosUDOELVmO4CglGTpJQIbGOgC4HT0HAaGi6HhlPXcBkamhDousDQBLomMISG1nnYmGmx83CErKbdJMefA1rmX9tbzrUl1B958yAPrVnSqzFwGhqBUIKOqElOLzUpCkU6pJR85jOf4T//8z+7ff7YY4/xu9/9jjlz5nD99dcjhEg7Fmx122Pf1XRS6aOFck8pUlLXEcWTRv4cTkiGXFle0n2DlLjaDmDpbsykvVooH5fNgok5LJmUx5LJuZSPz2ZWiZ8p+V7G5bjJ9znJ9TrIchl4HDpO/YTBAHAZGpOK8ghGQjgCR/p1HS5D5xNnT+RwS5jddYE+xxuaRn3HyPcoUJwerFy5kmeffZaGhgYAWlpaqKqq4vrrr+ePf/wjTz31FDfeeGOvY3sjKyuLQKDv7/FwooyGogdx06I1FE9rNOo6JUOunt9TMkSPtaJHW7CcfoJxk9IcNx6nbQgGo2FY6HfhyS5ENh1AS4T6te9FZUV4HDp/2VHX51i/y6CuPYqZtAY6VcUZzLx587jvvvu48sorWbhwIVdccQW1tbXk5eUxd+5cqqqqWL58ea9je+PGG2/k/vvvZ8mSJaMWCFfS6IoeNAVj7Khup8CXOp7xyBsHeHFHHf/76aXdU1Slhbfub0ghMIWLSCLJgok5GEPUIzwST7K7qgafP5t48WJ69Z+dxM9e389fdzfwy88ux+/u3b3VHIoxb1w2xdnpJeAVYxMljZ4ZShpdMaQ0dETTSqAHogle3lXPRbN6SoYYoXq0RBhpuAnFTUqz3UNmMAA8Tp3xJUVEOxowIo392ndVeSnxpMVrexv6Pk9nzYZCoeiJMhqKbphJi6ZgPG13vhd31BEzLa5f3F0yRCTjuNr3Y7qzj2dA5fvTS48MlGK/G6c3Dxp3I5KZV3BPL/JTVuznLzvr+lS09ToN2sMJInFVs6FQnMyoGg0hxCohxF4hxH4hxL0ptn9NCLFLCPGhEOKvQogpozHPM4lA1MSSMqU4YVfJkKknSYYYwWqwLNAchGImhX4nLmPov16aBpNLconFE+jtvQcNT2bV/FIOt4TZk0FAXNMEjQEVEFcoTmbUjIYQQgceBq4G5gFrhBAn18ZvAZZKKRcCzwI/HNlZnnk0BmM4tNRfi/V7G2gLJ/j4SZIhwozg6qgk6c4GwLQsSrKGLx7gcxoUFZcQbzqIFs88k+TCmXZA/KWdmQXEj7ZFsJSIoULRjdFcaSwH9kspD0op48BvgY92HSClXC+lDHe+fRdIIXCkGCosS9LQEU3ZZ9uSkuc6JUMWniQZ4mw/hNWpFRWJJ8n1OvGkcW8NFaU5Pgy3Dxp2g8ws08nj1LlkdhEbK5oIRnvPe3foGnEzSaCPcQrFmcZoGo0JQNek+6Odn6Xjc8CLqTYIIW4XQnwghPigsbF/AVLFCQJREzONou0HlaklQ7RYO45wHZbTXmXETIvSEcg60jWYPK6YRLgNLVSf8X5XdQbE12cQEHfqOrUdKiCuUHTllAiECyFuAZYC96faLqV8REq5VEq5tKioaGQndxrRFIxhpHFN/WHL0Z6SIVLiatuPZXhBCOKmhc+p99pHfCjJchkUFBaTqNtlS69nwIwiPzMzDIj7Oms24qaq2VAMnJ/85CeEw+Hj76+55hra2tpGcUaDYzSNRjUwqcv7iZ2fdUMIcTnwbWC1lFKpyQ0TUkrqOqL4UriV9tUH2FHTwUcXje8mGaJHmtDj7VgOLwDhhMm4XHd/yicGTWl+Fg5dQzZnXui0qryUqpYwe/sIiGtCICWqz4ZiUJxsNNatW0dubt9y/WOV0TQafwPKhBDThBBO4Ebg+a4DhBBLgP/BNhh9+xMUAyYYM0mYVg8dKbCFCX0nS4ZYJq62CpLOLADMpMSpa2S7hz7NtjccmmDSuPEkW6vQopk9vR2rEM80IH64NdznOIUCbHXaj3zkIyxatIj58+fzr//6r9TU1HDppZdy6aWXAjB16lSampqorKxkzpw53HbbbcyaNYubb76ZV199lRUrVlBWVsb7778/yleTmlETLJRSmkKIu4C/ADrwmJRypxDi34APpJTPY7uj/MAznX70w1LK1aM159OZ1lA8ZSyjriPK2weauH7JhG6SIY5gLVoyjun0AxCKm0zJ8w5KKmSgZHsd5OYX0F63C23yOT2UdU/G49S5eFYRr+1t4B8unN6rO83t0GkKxgjFzJQJAoqxy49+9CP27t07pMecPXs2X//619Nuf+mllxg/fjx//vOfAWhvb+fxxx9n/fr1FBb2VIPev38/zzzzDI899hjLli3jySefZOPGjTz//PN8//vf57nnnhvS+Q8FoxrTkFKuk1LOklLOkFL+R+dn3+00GEgpL5dSlkgpF3e+lMEYJmraU2dN/XFrNZoQXLdw/PHPRDKGs+Pg8V4ZlmW7cnJ9I7vK6MqEwgL0ZAjZ3sPDmZKrykuJmxavZxAQN3RBY0B5RhV9s2DBAl555RX++Z//mTfffJOcnJ7Nyboybdo0FixYgKZplJeXs3LlSoQQLFiwgMrKypGZdD9Rj04KQjGTaDyJz9/96xCIJnglhWSIs6OzqK7ziT4cNynJduHQR68HhUMXTBg3jqqjezGyipFG7xlcM4tPBMQ/smBcr5LpfqfB0dYIk/O9aEMoi6IYXnpbEQwXs2bNYvPmzaxbt47vfOc7rFy5stfxLteJ35Wmacffa5o2puTQu3JKZE8phpe2cDxl8Hpdp2TIx5ecyITW4kEcgaMkj3Xkk2BastdmTSNFnt9LbpaHeP2ejMavKi+lsjnM3vreA+KGrpGwLNojiaGYpuI0pqamBq/Xyy233MI999zD5s2bx4Sc+VCiVhoKatujPSTO46bFnz6s4azJeUwpOCEZ4mw/iGW4QNjPG6GYSWHW8EiGDIRxxSUEDx4kGWpG8xX0OvbCskIe3XiIl3bUMac0u9exbkOntj1C3ii64BRjn+3bt3PPPfegaRoOh4P//u//5p133mHVqlWMHz+e9evXj/YUB42SRj/DiSaSvHuwuYcM+qu76/mvv1Zw30fnH2+Tqkdb8TRswfSeCOi1hRPMG5+Fzzl2nj+a2zqoaurAMfX8Prv8PbR+P+v3dkqm9xLollLSEo5z3oyCtArAitFHSaNnhpJGVwyY9jQ1COv3NDA+x31CMkRauForSDpPrDqiiSTZbiO9wZASgg0QaoJIG8SDYMbAGl712PycbHIdSaJNfQsaruoMiG/oIyAuhEAiaQupmg3Fmc3YeTxUjAo17VG8ju5fg+ZgjO3V7axZPvl4gNgIN6CZIUzPCZdPNGExJb+72m03Nv4Ydr+QZqMA3QDNYa8GNAP0rn/vsm38Ylj6uYybLgkB40vHE6w8gJVdgub2px07s9jPzCI/L+2s45o+A+IOjrRGKMnxZDQPheJ0RBmNM5iYmaQtkqDA291P/0ZFIxK4eFanJIuVwNW2n6TzhN8/YVq4HRpZ6brgVW60DcasVVBSDsmEvcKwEmCZne/Nk/7eOabr+2gHbPk15E2FmZdnfG1ul4Px+TkcatiNe9LSXg3OVeWlPPz6fvbVB5ldmpX+mA6d5lCMcNzsEQNSKM4U1Df/DKYjYoKkx9P16/saKSv2Mz7XfqJ2BGsQ0kTqjuNjwokk0wt9qe/FkVZ44wEomAkXft1eQQwUKwnPfwneehDGLwFv78HtruQXFNEeOERLex3u3HFpx100q5BH3zrISztrezUaALoQNAViTC5QPx3FmYmKaZzB1HdE8Ti6B3WPtIQ52Bjiktn2KkOYUVzth44X8gEkkxJdCLI9KYyBlPDmjyEegku/NTiDAXYtyCX/DGYENv7EPn6mu2owvrQUo3kvSTN9LMLrNLi4rIg3KpoIxXrPjfd19tk43RJIFIpMUUbjDCWRtGgOxXq0dd2wrxFN2A2LAJwdlUhNB3FiXDBuCxOm7P9d8TJUvgnLPgf504dmsrlT7JhG5ZtwsH8pix6vh/FZBrHGg72OWzV/nF0hvq93af1jfTY6ImOz8EqhGG6U0ThDCURN5EmuKSklG/Y1snBiLnk+J1q8A0ewplssQ0oQQH6qeoVgg+2D2gYKAAAgAElEQVRGKl0AC24Y2gkvuAGK5tqrjUhrv3YtLColO1pNIppeeHBmsZ8ZRT5e2lHb5yrCoenUq1awijMUZTTOUOo7orj07quMvfUB6jqixwPgzrZDWIa7WxA5FDMpznLhPFmZUFqw4Qcgk3DJN/sUDew3x9xUiU43VT/QdY2ibA/xtiO9jruqs0J8X32w13HH+myYSdVnQ3HmoYzGGUjSkjQFYz1asm7Y14hDF5w/owAtEcKItWA5u6SrHpMMyUohGbLzOajeDOfdBdnje24fCvKmwtLb4NAGOPh6v3bNyS3EEzyClUwf27h4VhFuh8Zf+pBM1zWBJSVtSlZEkYInnniChQsXsmjRIm699VZuu+02nn322ePb/f4Tv6n777+fZcuWsXDhQv7lX/5lNKbbb1QKyBlIIJogeVJb16Ql2VjRxPKp+XidBkbbITuW0YVIPEm+z9EjeE5bFbz3c5h0Lsz5yPBOfuGn4NAb9mpj3GLwZNbMxuEwyPc6qGutw104OeUYr9PgorIiNuxr5HMXTOtVCt3j0Klui4wJzS1Fem6//faUnz/yyCNAevn0r3/968yePZsXXniBF154ocd+6di5cyf33Xcfb7/9NoWFhbS0tPC1r30t5diXX36ZiooK3n//faSUrF69mjfeeIOLLroo08sbFdRK4wwkVVvXbUfaaIskuHh2MSIZ74xldE8/jSUtik/u/22ZsP4/wXDDxfdkXIA3YDQDLv5nu7r8rf/q1655BQUY7YdsV1oaVpWXEjMtNvQREPc4dFqCcaKJ4a1uV5xavPbaa9xwww3He2fk5+enHfvyyy/z8ssvs2TJEs466yz27NlDRUXFSE11wKiVxhmGZUnq2mM9dJZe39eAz6WzdEoeeqQOIWW3jKlYwsLn0vGfXNS29Ulo3AOXf69fNRSDIn86nPUZ+OBROHQpTMvsyczn9uLTagkFmzCyilOOmVnsZ3qRj5d21nH1/NK0FeJCCISAlmCc8XmqQnys0tfKoC/59Ouuu47rrrtuUHMwDAPLsh9ULMsiHrddpFJKvvnNb3LHHXcM6vgjjVppnGEEYiamZXVzTdmihS2smFGIQ7PTbE9eZUQSScbneLovJJr2waZf2pXa0y8ZkfkfZ/EaKJwFG/9/iLZntIsQUJBfgNWUvp+4EIJV5aUcagpR0dB7QNzvMqhuC6uaDcVxLrvsMp555hmam5sBaGlpYerUqWzatAmA559/nkTCjoVdddVVPPbYYwSD9vesurqahoax39VaGY0zjJZQDP2kp+e/VbYQSSS5eFYRerQVLRnrVv1tmhKXIch2dynUM2Ow/vvgyYMVXx6p6Z/gmJsqFoC3f5rxbtk5OTjMDmQvhuZYQLyvHuIuQycUTxKKKxeVwqa8vJxvf/vbXHzxxSxatIivfe1rfP7zn2fDhg0sWrSId955B5/P1mu78soruemmmzjvvPNYsGABn/zkJ0+JvhtKGv0MQkrJuwebcRk6ji4ps/f9eRf7G4I8+pll+Ju2QDKOdHiPb2+PJJiS76Woa9bUuz+DD38HV/8QJi0fycvozqZfwqbH4cp/h6kXZrRLdV099aYPx/iFacf89LUKNuxr5Im/X96rzlRbOM7EfA/TCtOLIipGDiWNnhlKGl2REaF4kphpdTMYgWiCTVWtXFhWhMMMosfauxkMy7L1lrr1/67ZCh8+A/M+OroGA2DJzbbG1Zs/tsUNMyA3Lx89WIcwI2nHXJVhQNzvMqhujWBZp9fDl0KRDmU0ziBaQ3G0k1xTb+1vxrQkl8wuwhGswTqpaVEoblKa7cZxLAYSD9lFfNnj4JwvjNTU03PMTRXtgHceymgXn8uB2+3E6qXYr6zYz/RCHy/tqOs1ZmHoGqYlVStYxRmDMhpnEHXtkR4Nk17f18DEPA8z8gwcoVqsLgFwKSEpJfn+LquMdx625UIu+RY4xkjWUGEZLLnF1r2qejujXYoKipBtVYg0xX5CCK4qL+VgBgFxl65T16FkRcYKp5vLfagZ7L9Pr0ZDCBEQQnSkeAWEEJn5AhRjgnDcJBRP4uzSy7sxEGNnTQeXzCrCEbZ7aBzr/Q22ZEiRv0v/76q3Ye86WLQGSueP7AX0xZJbIH8GvPkjOzjeB9k+NxogQundTxfPKsJl9F0h7nXp1HdESShZkVHH7XbT3NysDEcapJQ0Nzfjdrv7HpyGXus0pJS9NxdQnDK0hXq6T96osG+YF80swBnYQtLV/X+3ackTwe9oG7xxPxTMgLNvG+7p9h/dYWtT/eELtpvqkm/2OtzQBLl5hbQ270dkjetmLI/hcxlcNKuINyrsCvF0AXFNCKS03X89ih8VI8rEiRM5evQojY29x6LOZNxuNxMnThzw/v0q7hNCFAPHfxVSysMDPrNiRKntiPZwTW3Y18jskiwmusKIYAK07p35vE7N3udYj4xYEK55YPA9MoaLwlmw+GbY8iu7bmTyeb0Pz/HT2tKIHm0h6SlMOWZVeSmv7Kpnw75Grp6fvpGTz2n32VBGY3RxOBxMmzZttKdxWpNRTEMIsVoIUQEcAjYAlcCLwzgvxRASTSTpiCRwd9GMqmoOcagpxMWzinB2VJHskjEFdjFfsb/zBrj/VVvvaenf2yuNscxZt0LetIzcVB6njsuXYxf7pXFnlBX7mZZBQNzj1OkIJ4iomg3FaU6mgfB/B84F9kkppwErgXeHbVaKIaUjkgDR/YZ3rNnSRVNc6IkA0ugS1JZgScj2Ojp7ZPwESubDwr8b4ZkPAN1pu6nCLfDuf/c5vCQ/l2S0DS2eOkTXNSC+v4+AuBC2rpdCcTqTqdFISCmbAU0IoUkp1wN9FoEoxga17RG8jhOuqWPNlhZPyqXYasQ6yd0UNZPkeh24dAEbfmj36b50gD0yknG7B4YZs8UNRyJAWTTHDtbvXQdH3ut1aJbbgTA86G3pPa2XdAbE+6oQz3I7qG5VrWAVpzeZGo02IYQfeAP4jRDiv4DQ8E1LMVTETYvWcKKbnPmeugANgRiXzMzDEarDcpykZmtaFPldsOuPUP0BnHsnZE/o/8kTETsOojttY5GI2l33Qk1dXs2dr5YTn4VbbD2pWADiYdvg9JezP2P333jjAVsRNw26BkX5BZiBWkQidWc/n+uEZHpvPcQdukbUTBLoo8+4QnEqk2kg/KNAFPgqcDOQA/zbcE1KMXR0RO2sqa5qra/va8RpaFxQEkeGRTc5c8uys4H8sTrbvTNpOcwdgMpnMgGxEExa1rPnhZW0X7LzT8u05cqP/T0Zt/dPxu1XLABmFNw5mZ9fd9pFf3/8Irz7c7joG2mH5vld1DUYeILVJPLKUo65ZsE4Xtldz2t7GrhuUfomU4am0dAR7a7TpVCcRmRkNKSUXVcVvxymuSiGgYaOKC7jxCrDTFpsrGjknKl55EaP9kizDcdNCvxOjPd/bldbX/RP/e+RYSXtFUW6Jkma3j9XVyICh9+xVxxGP5oeFc+1mzZtewqmXwwTl6Uc5nZo+HLzSLYeQWRPQeo9+5/PLPZTVuznxR21XLtwXFrJdL/LoLY9yrRCfzclYYXidCHT7KmPCyEqhBDtqrjv1MFMWjQF43i7tHXdeqSNjqjJZVNdiKRpG4YuJKWkKLQPqt6y5cd9qVNR0yKl7W4qnA1ZJUNxGXbleckCWyqkv/GCs2+D3Ml2wyYrfWZTSbaPuJVED6eXpr5m/jiOtEbYUZP+q69rgqSSFVGcxmQa0/ghsFpKmSOlzJZSZkkps/vcqw+EEKuEEHuFEPuFEPem2H6REGKzEMIUQnxysOc70whETZKW7KY3tWFfI36XwXlZjSSdvm7jzaTEqYFn86PgyYf5n+j/ScPNkDsJ8qYMdvrd8RfZMYpwc//2M1yw7B+g/WivfcWzXAa4stHbDqU1LheUFeJz6by4o7bXU7oNnZq29GKICsWpTKZGo15KuXsoTyyE0IGHgauBecAaIcS8k4YdBm4DnhzKc58pNASiJyRA6Gy2dKiZC6Zl4bJCSKN7IVokkWRi8ENE/XY7kNxfbalIG3jzoWj28LR9LZgBLn9GMiHdmHqBbXC2/Dptq1dNg5K8LKLRCEY0tWFyO3RWzinhnQPNtIZTa1YBeJ06jcEYMVPVbChOPzI1Gh8IIZ4WQqzpdFV9XAjx8UGeezmwX0p5UEoZB36LHXA/jpSyUkr5IaBEffqJZUkaA7Fu0hfvHWohmrC4fHwCS+9ZuZxMJsjdsdbOlJrzkf6dMN6ZJVWy4Hi8ImYm6Ygmhk42XNPt45sxO1CeKUKDxTdB66FeBQ3zvE4Sug9He2VaN9jV80sxLckru+rTn04IBHYrWIXidCNTo5ENhIErges6X9cO8twTgK7a1Ec7P1MMAYGoiWnJbsHY1/c2UOR3sMTfiuXo7pqKmxbjG99Gaz0Eyz7XI9bRK2aUWCxGW+48qgMmO6vbeWt/E+8caOaDyla2V7cP3VO3y28XGoZb+xffmHEZZI3vXG2k3s9laOTmZBGPdKDFU3f2m5jnZeHEHF7aWUeyF2PocxpUKxeV4jQk0+ypzw73RAaDEOJ24HaAyZMnj/JsxgYNgSiGduKZoD2SYMuRNj4+14fQoj3cR9FYlNKKJ239pumXpD2ulBBPWsRNi3DcJBCOEg200Ja/ELM+gYaJy2FrVh0zWB2djZ4WTMghayhSUbNK7VqOYJ3tDssEzbBXG28+ANWbYGLq2tTiLDf72534A0eIulJkfmEHxH/w0h42VbWwfFpByjFuh05TMEYoZuJz9UviTaEY02T0bRZCPJji43bgAynlHwd47mpgUpf3Ezs/6zdSykeAR8Bu9zrA+Zw2xE2LmvYIOe4TqaNv7W8iaUmuLO4g6Twph0FC0ZG/oIfq4eJ7jiu+HjMQsYRFOGESiJoEoyZW55O6kBKv2QLFC8nJKk47n2y3g0g8yaaqVuaNyx68qJ8QUDTLTutNhOEk3ay0zLoSNq+1BQ3TGA2f00B3+SDYgJYT6rEiAzhnWj75XifrdtSlNRpgK+k2BWLKaChOKzJ1T7mBxUBF52sh9k3+c0KInwzw3H8DyoQQ04QQTuBG4PkBHkvRhaZADCnp5prasK+RKblOZmQle9RIxMIBJhx8FiacdfxmmrRgf2OQ7UfbqWgIUNMWJZpI4nUaZHscZLsN8uiAwtnIrNI+5+Rx6mS7HWyvbudgY3DwcQ7dAeMW2AWEVoYV2LoTFt4Itdug7sOUQzQNSnI8hEwwQjUpxxi6xpXlJWyuau21+ZLPZSvfqlawitOJTI3GQuBSKeVPpZQ/BS4H5gDXY8c5+o2U0gTuAv4C7AZ+J6XcKYT4NyHEagAhxDIhxFHgBuB/hBA7B3KuMwnLklS1hLpVJDd0RNlV28HKCSaWy99jn/yDz6HH22HZ7YC9wjjcEqI9kiDH6yDb4yDLbeB26BzzeBnRVhK+cSSyMncHOnSNQr+LquYwO2vbiZuDzG9w50DxHDu+kSlzrwV3rh3bSEOez4npzMbRUY1IppYwuaq8FCHgpR3p9agcukYiaRGIKlkRxelDpkYjD+h6t/EB+VLKJDBgWU8p5Top5Swp5Qwp5X90fvZdKeXznX//m5RyopTSJ6UskFKWD/RcZwptkQRR08Khn/hfu6Gz2dLlpVGk3r2iWkTaKKn8I3LaxfYNGKhui9AUjJGTJv6gxzpIunKI5c3qd2qtJgSFfhdt4QSbD7f2quWUETmTwF9sp/tmguGGhTfAkfehcW/KIU5do8DvJmImMUKpi/0K/S6WT8vnlV11vXbsc2gadR0qIK44fehPcd9WIcTjQoi1wBbgfiGED3h1uCan6D+Hm0N4Hd3dTxv2NjKvUKckp2csIXv3U2hWHLHsHwBo7IhR2x4hx+OEFPZAS4SRmkG0YN7AVG87yfU4EcDfKltoCgyiv7YQtlwIwtanyoR5HwOnv9fVRqHfRUTz4wxUpi32u3r+ODqiJm/tb0p7HL/boE61glWcRmRkNKSUjwLnA88BfwAukFL+r5QyJKW8ZzgnqMicUMykNZzoVptR2RSiqiXMFePjPYK6RqiOwiN/wSy7GnIn0RqOU9kcItvtTLmAEMkYIhkjWrigx4plIHidBtluB9uq26lqCg1cUtxwwbiFEA2kLd7rhtMH8z8OlW9Cy6GUQ/wuA5fLiRmPpS32Wzwpl3E5btb14qI61gpWyYooThd6NRpCiDmdf54FjMOuqzgClHZ+phhD1LZHME4SyXu9s9nSxRNED1dS/q5fg9Awlt5GMG5yoDGE3+1AS/WtsEz0WAfRwkUpM4oGikPXKPS5ONAUZFdNx8CfyL35dsV4qCWz8fM/Ybuqtv4m5WYhoDTbTVB4caYp9tOE4Or5peyu7aCyKX2nAI9Dp7o1tey6QnGq0ddK42udf/6oy+uBLi/FGCFuWlS3RbrVQVhS8sa+BpYVS7Kyu6vZOtsPkV29gcjsjxF15VNRF8Tj0DH0FEsMaWFE24gWlJN0p65dGAyaEBT53TSH4mw53Eo4PsA4R940W1U3moGWpjsH5n0UDrxm61KlINfrtFdUiSB6LHWx38o5JTh0wbpe9Kg8Dp2WUIJoQsmKKE59ejUaUsrbO//638BHpZSXAuuxazTSNyhQjDip0mx313bQGIyzcoIFonv8oXDXL0kaXuSiNexvCKJrAqeR+utgRFqI5UzF9PWdWjsY8rxOLAs+qGyheSBtUzUNSsrtPh3JDCQ8Fv6dHZfZ9lTKzQ5dUOB3Ekw6cHRUpRyT7XFw4cwiXt/bmNbYCSEQgoFdk0Ixxsg0EP4dKWWHEOIC4DLgf7ENiWIMkCrNFmDD3gbcOpw3pXvxm7tpB776D2gu+yRHwwZJS+Jx9gxqi0QYR3slluFGOvwY4cbOV0Pnq/7EK1SHEazDCNZ2vmowgtUYwRpEJjfwTnwuA5/Twbaj7RxpCfc/zuH0dsqMtPUtM+ItgNkfgX1/sXuhp6Awy0VC92JEW9ASqV1QVy8oJZJIsmFfY9pT+V0GR1UrWMVpQKalqsfW1R8BfiGl/LMQ4r5hmpOinxxLs/W7ThiNRNJi4/4mzi9N4nZ1CVpLSeGutcRd+dRPuoZE3EzZZU6PNOFu2oXU3UiHD3fLLui838nj/xXH33Xr/icFERN8DhBWkqQrpzN43rO5USqchka+10lFQ5BgzKSs2I+hZ/p8g52CmzcV2o+AL33FNgCLboTdL8C238KKu3ts9jkMPE6NWEzDEagmlj+rx5jZJVlML/Sxbnstq8pLUzZochk6TcEowZg5NFIqCsUokekvsVoI8T/Ap4B1QghXP/ZVDDNHWnqm2W453EYgluSyKd1vUL669/C07KFi4ieIWEZPgyElRqAaV2sFluElUrwY01uE6c7H9NivpCefpKeApCefuCuf/bFcXqr189NdXr78lovr/qzzkx1uku48KuJ5/OtbYSJHtqYtlEuFrgkKfU7qO6JsPdLW/0LAghng8vXaHxywdazKroQ9f7L1rE5CCBiX4yGAF0eoOmUfcSEEV88fR2VzmN116WXb7VawykWlOLXJ9Mb/d9iV21dJKduAfECl2o4BUqXZAmzYU0O2U3L2xC6ZTjJJwa4nCHvGU1V4Efm+k9JmrSTOjkM4Q7UgdBI5U5HGidVBIinZ35rkxQNxttXb/vtNdSa3vxTih+9FefFAnKSEK6c5uGiSPZ+qDot36wR3vBJn544t/TIcQggKfC4i8SQV9YH+uXZ0w5ZRT0T7lhlZfJM9ZvszKTdneRzouk4SA2dH6hTdi2cV4XHovLg9fUA8y+2gpj2iajYUpzSZqtyGgf/r8r4W6L19mWJEqG2PoJ/kDonETN6rbOPKyXRLwc0+/BquwGHenHoX4/OyuhXviWQMV/tBtEQEy3ADOqangH0tSf68P05Fa5LKdotE5/3umukOFpUYzC00+Odz3ZTl6UzM0nr0xb5ksoPJ2Rr/8XaEe980ubFhE5+6aDG6K0ORQewspvpAjJy2CBPzMt8Plx+Ky6F+O/iK0lev506CaRfDrudg0Rpwdxd0dGiCIr+TpoAkN1xPwj8Ry5XTbYzHqbNyTjEv7azjHy6cTo4nhctPE5iWRWNHjPF5/WxwpVCMEZSL6RQmVZotwMad+4kl4bLpJ1YZIhknb/dvaPFOp63kPLxdlFe1RBh3825EMk7S6ceKR6l2TgIhaIlYvHnUJMspuH6Wk2+f7+Hxj/j48jK7ujzLKbh8qpMpOXoPg3GM6bk6D13p4+rpDp7aa/Fvz22BRP+kNfK9TvbVB/pfJJc9zm4qFelDn2rJLfacdv5fys0FfhdJCZbhxdVakTLIvqqzQdOru9M3aMpxOznUHOq1F4dCMZZRms2nMKnSbJORdn63tZFZeTrlhSfiHL79f8IZbWLnrNsp9LuPP3Tr0Vac7QftgLfhIhEK8P/tncbBkOSRqyXLxhn8/np/yuBuf/AYgq8u93BWqUEyHsHbtI1Q4SJEhi1ldU2Q5XKws6ads6fk4TIylDARwm4/G26xO/4ZaSrZC2bAlBWw4/ew4O/sLKwueJ06WW6DcFLDH29BjzSR9BZ1GzOlwEf5+Gxe3FHL9UsmdOvNfgyHrtEeSdAcjA1eIl6hGAXUSuMU5ViabVaXjCmsBG9s2UldWPDpBa7jN3orEqSg4nc05S6kNXc+WR7DDniH6nC17cdy+JCGi1g8yb07xvF2g4Mb5rjwGAJdE4M2GF25eLKDy2Zmg7R4/NXN/PTV3RkXvbkdOpYl2Vcf6J/cuO6wDUdfRX9LbrH7j+9OrdA/LsdDzEySdGXjaqtIGSu5Zv446jtibD6cfmWT5TY42BRSkumKUxJlNE5R2iMJYqZ1oiBPSrSmCn69O8mcfI3l4+xFZDIpcex6GqcZZN+UNbidGi4dnB2HcQYOk3TlgGYQNgX3bMphU6uHbyx3s7oss/TYgZJ0+PAaklf2NPPVpzdzsLGPLKdOcjxOmoIxjvZXlsNXZMc4UmQ/Had4LkxYCh8+ba9KTiLLbeBx6MSkAy0Zxwj11Jw6b0YBuR4HL25Pr0flMnQiiSStYdVDXHHqoYzGKcrh1jCeLmm2RqiOV/fU0xAR3DrfXmVICc0NNUyuXkd90Qqa3VMocAtcrfvRo00kXXkgNOIWfO39bLZ3ePjmeV6umj68BgPszKjblmRz/4UakWiMrz+zjRe21WSUIZXncbG/IUhbf266mgZFc+ymTb2x5BY7/rHnzynmbK82wgkT05WNq/1Aj2wwh65xxbwSPqhqoaEX9V6fw+DQYEQaFYpRQhmNU5BQzKQlGDueZqvFg2hNe/j1fidzCnSWjTNAQn1HlPGHnkGTJgenfAo9GaUgdADNjNjZP51uJ6dIckFBgH85z8ElU0a28GzRBD+PXK6xtEjyyJsH+cOWvjv+6pog2+NgR017//ScPHl2sV9vtRvjFtkV5dt+C8meQfdcjxOnrmFK22A7Akd6jLmqvBQp4S870wfEPU6dQNRU6reKUw5lNE5BatujGMekaK0E7uadrDvqojEs+XTnKqM5FCfWXMWUxvXUlq4khIfxsYPouobltPtpNUU13qx3oseDrCl3c97kfqSzDiHZfj/3rdD52mLJVWX23PoSLXQZOgLB3rp+xDeEgIKZEI+klxgRApbcCqEGqHi5x2ZNg/E5HkJxk6QrB2fH4R7yIiXZbpZOzePlPho0eRw6Vc1K/VZxaqGMximGnWYbPp5m62o7QCIW5cm9knkFOktLdToiCeo7Isyv+T1SGFSXXIa/Yx8enw9p2Bk79RGNu9/P5T+3Z9OWdGF6SwY/OSntfhaWaYsG9mdXp49rZjgobv+QtrYW/vHXm/n1e1W9pqZmux20huNUtfThcuqKO8euAo/1EhSftBwKZ8HWJ1MGu/N8TnQhSFoCy3DhaO9Z8HfN/HG0hRO8ezB1Lw6wdbZaQnE6omq1oTh1UCm3pxhd02yNUB2OYDW/r8mmMRLj6+e4iMbt2o2S+GFKm97m6LgrcMTbCDqycLns9NaasMZX3s8jYAp+tOAonvxJJLt24bNM0OyvxoSN38QZOIKQlm0QpAQsjl70APHsKRRu/wW5B/8E0kJw4gbfsOAO2mdchyNYg7tlN4FJl/XZGlY6vFhCkN+2g7MmFvD0347w4dF2vnHFrLTpqXleJ4eabLHGAn+GjaEKZkBVvX09IsVzkxB2bOOV78LBDTBzZbfNhiYozXFT0xYh25OFM1yPGZ3YTTZ+yeQ8irNcrNtey4VlRSef4TguQ+NoS5h543PSjlEoxhLKaJxCdE2z1RIh3C17CDtyeWp3lPJCnfkFgsrmMG5DZ9bepzB1Ly05CwiKLPweA01AVVDnq3/LJW4J/mtxDWWFHuLHqpstk5xD68iveJYjFz2A6S0mUriQuH+ifXMVGhK7mVPSYbuRIoULkbqr83N7jCmh1TeDUCTBhIoXKK16gazDr9G4+Isk/ON7vUZpeHC54VvzmlgycSoPvVnD15/dxgOfXERJCsOhCUGO28mu2g6WTc3H7cigfsPps3uLd9SANy/1mKkX2KKHW34NMy7tYVwK/E5q2iJYFphOP862fURKlh4fp2uCVfNLeeKdKg63hJmcn9r153cZ1HfEmFJg4nOpn6Ni7KO+pacQx9Js/Q6Bu34nluFm3SFJc0Ty9WVOjrbakiLjm98lv+1DqksvJ+Ypxoqb+N0GpgXf2pyDJeHBpc2UuSJE/DMAia/2fQp3PoYzWE24aBHCsl0mLXPW9DqnYOk5NBcuJZGUWFIihN3GNdfjYILLwDn+y7R/OBXftkeZ/NpdtMy+kday60FLH3CXhgcLwTVZlUxbPYd7XjjIv/1pFz/51GIcKdRunYZGzBTsqmln0aS8tJXp3cibCh1H7f7fqXqdC83WpFr/fah6C6Ze2P2cukZxlpumYAy/24MRbsYIN2L6Trj5rphbwpPvHebFHbXccTHtPyYAACAASURBVNGMlNMQQuDQNarbIswqyUo5RqEYSyijcQpxuNVeRbjaDyKSEcJGLk/tCjK/UKfIESOWlEwI7WLu3ocIu8dRW3IxSSkxdO14BfW3FnaQZUimGa3E/ZMwok0Ub30Yb9OHxP0TqT73XwiXLE3rSrIsiCeTxDpVZzUh8LsMSrIMPC67juHklrOusz9BdOaFmG/+F4W7n8Bb8w7Vl/wotWuoE2m4SQJzzT18+/IZNMQcKQ3GMbLcDppDMQ41hZhZ7O/7H9PhhrwZ0HrQbhWbihmXwQdr7dXGlAt6/JsUZbmoD0RBQtKVhattP6an4LhrL9fr5PwZhby2p4HPnDc17Sooy21Q0xZhcr43s5WSQjGKqED4KcKxNNscsxlH4ChJVy5/PhCnJSq5dpogalr8P/bOO0yyqzzzv3Nz5eqcJ+fRjIQSkhBKCAEyLGEJIidjbGOvwRG8XsA2rNdEm8cYezFgAzZgMF4wiCiDEEFxpNFIk0NP6Onc1ZWrbjhn/zhVHWa6RzM9o4T7fZ56qrrqVtXtW/ee94vv11PZz0W7P0poJ9m37i0ow8YPI074CT70SIpIwdZsyEqvgjQdwngHIHBKJxjb/naO3vQ3VLqvmD8bQ0LVjyhUA/LVgIofErdNVrXF2dyT4pL+LBu6knSmPVKudRphNOFlOkm+8IOUb/hzpgZuJl+LUIG/6GAjaBCHHedq+yC3rNIL8SND+UV7G1riDkcny4yfoT9iHrL9eqLhAqW1gF78L3kNjO+DoftP/59sg7aEQ7keokwHIQPs0vyS4Vu3dVPxzzygyRACUwiG8+emx7WMZTwZWCaNpwmG8zWcqIo3tYfQy1CP4Ct7fDa3Cno9n+7KIS7a+1cA7Fv7FkJbhzp2Fzze93AbO6dsCr5AhHUyg9+lc9f/BSKCZC9Hbvks+TUvmrGQQXeST1d8qkFIyrNY3Z5ga0+aSwayrO1M0p50STgWxjmeQYkNz6b7qlfSl42R3PtlVvzw10kO/WzRElhlukROktjETh7ef5j3/PsuvrZj4ZnehhC0xB32DBfObs64aesS3DPJi2y4BRLtsOMLC77cmXYJGhVeoZvBzQ8iwlnS2tKTZmVrnO88MnzGRr6UZ3NsqnLuc0OWsYwnGMuk8TSAH0qGpgp0lA8gLRcMm281vIyb+wJ6a4fYcvBT2EGRA2vfSN3T1Tr3Trp89EAPPXHJJ66coi93Lz33fpD0iR/hJ3sxwoZla1infV/JD1ndluDi/iyr2xO0JhxijvlYBVBnBcsQ9GQ82rbciPRa6LnvL+i6+8+xKgtb48p0CN0sV7uD3LAqzud/cZS7Diy8rW0a2KbJ7pMFwrOZW5Hu0SKGC8iGAGA6sP02GHkYhh8+7eWEY5GJ2dR8nRtRQuAUj828LoTgBdt6ODRe5sDY4k2FpiFmGjKXsYynMpZJ42mAyVIdr3AEW1aQdoJaqPjy7jobMhHXuwdYP/hF4tVhDq16NeXESgDumYzxsQOdrEwEfHrzg2x55KO07/1npJ3kxNUfYOTKP0Y66dO+q1wL8SPJxu4U7Sn3gpDEYnB7NuO+4v9SveztJCd2suKO3yBz4Bu6FPZUGBZRvIX3bM1xUYfNx3+4nz3DC3sISdeiXA85PHEWelaGqXsyzuRtbH4heFm4/zMLekQ9GY9aqPtSIjeDXTqBMafr/MaNHXi2wbfPMKAJdN/J0cny2ZHdMpbxJGGZNJ7ikFIxdOIoLfURQleXh/77vjrTdXhd5yArT36bTPEARwdezHR2K6DXtduHU6yO1fj4FdNkohxmUGRq7UsZuuYDVLsuOf2LlK7Ocm2DLT1pUk9U+adhEbvs1ciX/yNB5zacsYco1xZpDBQmRrKdD1xaoSMm+MC3dy+aB2iJ62qysbOx3JOd4KUWFzO0PLj8LTC8Ew784PS3uxYJx9KhJSGQpoeTPzxDMHHH4oYNnfz0wATFMzTyWaZBECnGi8sjYZfx1MUyaTzFkc9PY409ihFvASEo1SK+uqfG9mSR5wQ/omNqBye7bmS8/SoASqHAiqr8beqz/Evmk2RcqHZczMilv0e55+pG8ns+pITpqk9HymFDVxrXeuJPCyvTg/fCD+E97/0kYzby2D20PPyZefkBAIQg0dLGX17l0xOXyGBh0UIhBNmYw56RIuX6Y+Q3hID2jWcWM9z8Qq2Ce/ffavn0U97ek41R8TXZSSeJVZ3ArE/PbHPrtm78SPKD3YvrUQFkYvbykKZlnBuU0sUcfgX8c1BHWCKWSeOpDBkxfugBbNdFmTYyivjXHScphgbvbrmDvpH/ZKL1UoZ6bkEp+OfBFHfuPMjW3R9l5dTPcB17JtQjVISfWXla2agfSgo1n1WtCVa0JDhDVevjDyHw4gnWdSZZGQ7SfvjfGbjjN/FGHjxt0+72Vv72uoj1wT78WmVBjSfbNHBNg0dP5h875NMUMzyFEGb3zYBrf1fLj9z3D6e9nPFsXEsQhnqxj5xkY8Kf/t7V7Um292f42o4TlM5AYrZpUA8jJkvL3sZ/echIz7ivF/UQsdI45Idg4iCM7ILj98KRu+DgHVq54OjP9HOPs3Lycp/GUxiVkf1UC1PEW3sgDBg/todvDfXzptS9XD3+NfKp9QwOvIwIwXf3F3l96TNcZhwg76zg8Ko3k+jSDWVGvUgY70TaifmfXw+RCjZ1p0l5C5wKYV1rSAlzptt7wUa4xwHeVW8lXHE55p0fof/u9zFy0a9RWvfCedtIL4OsFXnv13fQ1dbCO2/ZctrAqIRrMVmuc2CsxKbu1OIDpZpihsfuASe5cJ9K+3rY+lJ45Ouw4fna82jAMLRs+tGpChnLRlkeZnUSqzJGmOgG4K3PWs07v/IQX7nvOG+9dvWi/3vSsTkyUaYj5S6+v083hD5EjVtYg3pJqw0rqYsNTEeHAS1HF2YYVuN8azw2zMZzT9PjIaPGLZzVZms+F/naU4jqeuRwWNfHaEb3rPk/K/3/zz0etqcVDprHpTyhSeNxPE7LpPFURWmc3Il9yFg7RlChOrSbbx1Ps1Ie43+Gf0sl1s3B1a+jpmz+an8btxTvYoM9wsH+lzOcvpj+Vk0QIgpBCILEHPkOBYVaQNwxWdORnB+OkiHUivqkdhJgxfQJHfoggwUE/OaenA0LR4hZojEMsONnbORbDFbvxfCKTxN+//30PPJ3jIcVpje9ct42hpfiiu4S/7g7R0/qALdds+G0z2mNOwznq5gGrOtIYSzWMe5lIN0LlXGd+F4Il78FDv8YfvpxeMmn5pFoS0LnUaJIYZqCyEnPafizWdOR5ObNXXzr4ZO84KJuerMLj7r1bJOJUp1cJaA18fjPNrkgkFIvemFdny9BZZYY/AqoEH2uKH1vWrrkWRiNBTJqaJtFDUu58RsJMb8wwrB0tZthN4jGnV1EhaHPO8NsnIOG/hxhNP4Wjb8XeA0a36vm3ys557lFtmneR37j/59DkFGg75vbCQFzHYHmqWiYs/tuWOCll3TNPBFYJo25qJdgfK9eMGLZxqLpPbHWTRSAXyIYeojRMEaaEuHwfk6WDHaOK77kfghpxzmw5g1kpx7iJ8MZHig/l8tX3sSBzsspSpvOlIfZiDMZQQk/swZl6p9aSk0Y7SmHgZa4bsZTSl/cYU1fjC0rdXLYXUDWYkbJNpq1lmbu5aw11bxYwhqUx/X7vJS+0M8Flof1/A9QufOvmUyux5yznjTxmm0JTpbL/POOMXqTBtdtXzfvdSEE7QmXk9M1wkixsTu9uNRI62qtSbWYmKGTgKvfAXf8Gez+Blz0stldNQQ9WY8TuSqZmI0ybURQxC4NEaRXAfC6q1by04MTfO7nR/ift25Z9N+OOyaDk2Va4vZTz9sIqvpaqeX1eVMvQVSbs9ir2cXPdCB2ARfAGXIJwa9DbRqQeiFuLvBwSohmzvET4pTXTg3lnOWxnsN/M5b9XG+8SWCnegK/BHhSSUMI8XzgrwET+Ael1P855XUX+DxwGTAJvEopNfi47ZAMtHvnF2HqiD4hTBtirbrBy0mAndBW0oVAWNcWmV+B6rSeGBdUQQjydYFVmYTKECNVi7tzcT5pfJiYEXK898WsP/JFEpUTPN/Zhlj3DJ7VEVAJXOKOQaIRahJBBemkCD0tkxGEknI9ZEVbnM6Uh4hqUG2Uhia7INOvre0zhaCaXsS5hKlCH0pjkDuiFxo7ro/l2cKwiN3we3hTZSaKNVYN/QfTq25F2fHGLgneeWWCsWqZj981THsMtqw/nTjaEi5jxTpBlGdLb3phWRInoXWp8scXlxdZc6Oe7HffZ2DN9RBvm3mpLeHOCBkaxmzDXxjvRlkerQmHl1/WzxfuPsrDJ6bZ3r+wRxN3LCZKdQrVkEz8iR2MdRpCX5NDeRJKo9Ds7zEbpGA54J7D73k+MEz0cvEkH5P/whBP1rhJIYQJ7AeeC5wA7gNerZTaPWeb3wS2K6V+XQhxG/BSpdSrzvS5l19+ubr//tMlH84K1RyceEAnRJuQobaWgzozpoWb0iTiZc7OG1GqEatsJLWqOb14Rj4zlo3ViOmaNjIIOHjgUYzKBCfrLlIpso9+ns1ikGp6HdnCXkpGmtGBW5lquViXeSqohyH92TiWZYCSmPUCtbatSDtGtR4RKcW6do8UVe0duCnIrtSLo3WWsuLnAyn1/547ohN7pn1Obngk4djee1n1s3dTT6/m5NXvJ/JmVWqLvuJ3flBie2vIb183QJBeveDvkqv4JFyTi/oyM5pc8xDU4OhPGwS6iIEwfRy+9hZNGjf9ybyXjk9VG0KG+r1mPU8Y66DeugmAehjxG/+8g6Rr8fFXXrKo11OqhyRcc1Fiedwgo8Z5Oq1Jojl7xLQ04Z+rt/gkIJIQKUkUKUKldPRMSvxIEoQSP5T4UhGGEYFUCASWKbBMA8cQ2JaBbRo4loEhBJYhMAwwhYFpaNmXc1VDeEJQnoC1z2EpOyeEeEApdfljbfdkehpXAgeVUocBhBBfBl4M7J6zzYuB9zcefw34GyGEUE8k0xmWTow2pt3NxC6nj+mLC6UvonirtjidhLbEg6q+2Ko53TimImbiqZYHThyMRnNdWNfWW3EEqtOUSwWCUo1cEMMyFJl9X2Uzh8i5fbQU9vM5eSufjl7C/8nkiAl9KOphSEvCnUcYfrIHacXIV3yS1FidtXANAZmV2rNwz0LY74IeS0MTcrNKKT+klWYVZxW6Mg3o3XA5R6p/zKqHPszAT36foWv+jCDZB0DKEXzsOQnSjsLJD2KEdeotG07zilriDoVawM7j2tI/TSTQ9qB1HUwenG9AzEV2QOtS7fgn2PgC6Lts5qWOlMtIoTZjY0ROGrs0TJDsRTppXMvkzdes4kPf28cde0e5ZUv3gl+RdLW3UaqHJB/PvhkpIShDNa8nFlam0PF3Q5+nifbH77uXAKXAj/TCXw8jqkFEEEmCSOGHkiCSSLVgtk0v9gKMxsJvmyaerSfBRFIhpaISSWSjSCSSqhEeVMwJvgFgCF3t1iQaADlnHxUKqYBIoYhASqQMESoiMhyksBBBFTMogQoRUYAhfUzpE7othMkeLD9PZvReTOljRD5C1jFlndBtJb/+pRhA9z0fwAiriMgnf/W7uQDj1M6IJ5M0+oC5A5ZPAM9cbBulVCiEyANtwMQTsocLQQhtlc+1zGWoY6ul0TkhUjWbtItlZq1pJbXHUcvrWzWv4/8CQgQTVcFYxabQyDevH/wSHf6jfNp5La0dA3z2SAujZg9/snWMmKm/LIgktmmQ9mx94gUlgkQPgZWlkhulI+HQN7ASKzug8zVPBRPJTUHnJmhdA6URmBrU5GrH9UK12Nssg85tN7DXSrHhwQ8y8JM/4ORV76XWsOKznv7fHihm+Ld7xvmTZ/vIzi2nSbGnPZtiLWDHsRwX92dPn2WR6YPcoP5tzEVCIZe8Rjf7/fSv4OWfmSE9zzZoTzlMlwPtbQg94c+dPkS14xIQgmvXtfMfO0/yhbuPcu269pl576fCMQ2OT1XY3HN69/55wa9oo6Y8DqWJ2US1HdMG0IWKwctQeyyVSahO6e77eBsc/Tns/16jkkjO3lZfB5tfBNNH4c4PI2WEkhFKSqSMqCX6OLT995FKsfln7yQVVUk3ksyikZAevPnvwY7Rdf+HSYzuYDZhLRHA8BV/RKXrcrIHv0Hb7s8hFCgBzcT49JoXMbn1TbjTh+j76XuYMfYa9/XMaoae9UGUgpU/fDtG1OglUhFCRggl2Xfz51CWx4r7PkBq9N7TDsuJK99LuftKWo7+gM7dnz3t9am1L2N861twi5P07frk/ENqOFRaNjK26sWaymp5JCBNl9F8mQ6lHtdeil+KRLgQ4teAXwNYsWLF0j8oCrRn0ExkGeb8qobFwiineiNzIcNG3qJhydXzjQsEvRg1vI6yHzE4WaZQ8QmkwgmKbDv2eRLVkxyRXQy2XMNfHsrS4wV8YPMoba5uJFNKk0ZvSwwjKCGkJIj3EAiXQqDoWXcpvb19iCci/LQUWA5kV0C6vxG6Oqxd7DNUkCQdi661z+BR6y/Y/NAHaNvzRYau+fN5C13eh1+MGnzkFwXec9WD+B3bZ0bdNpHybCp+yIPHclw8kJ0ZoQvo36Z9PYzuhuQilrblwrW/A9/5I9j5Fbj09TMvdaU8JoqzjYfSSWJVJjBrU0SxNoQQ/Oqz1/B7X93J1x44wRuuXrXgV6Q8i9FCjZVt8UWJ5awgpSaJypRO9DfzEparvbxzLaUOa5oIKpP6MytT+vGlb9Cf+bNPwOEfacKYm2y++f2w5gZtMOWOaDIXBqpxq1dr5As1/KkaLaGBRJfeKqsx4MtrJ+FaCAFB20ZCGQAGaqYiCoRhoKARmk0yd3gYCMKYbnCtZdcyvfYlc5LjmlxqrbqUOnJSFFbcjCYkZqq4wpg+H4SAaucliKjxOxsmSpgoYeDYJso0KPc/Gz+7Vu9DYw1RwiTMDGAYUO26lFE3qd9nWCjTQ5ouYaJL58Syqzlyy+eQlquHnRnOzHnevKJPXv/hmcOrciPn9jsuAU9mTuNq4P1Kqec1/n4PgFLqL+Zs873GNr8QQljACNBxpvDUknMaUQj/8gp9cXVfBKleMJsXUuOkEgZYdqPcr3nvNB5bsyQjI11RUs01pCmaZYauXiTnLIS1IOJ4rsLgZBUBpFSZ7uIuBoa/h6FCDqg+3uu+m0cqWXpjIX+0cZyUPVuCWA1C0p5Jh1kBYREke5l2+6gketi8sp+Wp0vJ5lycFrpKL2jtH89VmRgbIZ1wkU4aI6gg7Vkv5V/31Pn0zjqv3gBv2yqoZ9YQxttP8zqqfkQ1CLlkoGV+0llG2iI27TPnfH7wPjj2C3jFP+qS3QYOjJWo+hExR59HIqwhZEi189IZAvvo9/fxs0MTfOq1ly04mRAgX/Xpznis6zzHIU2hr4miNKa9YBnq89NJnHteIqhqz6tzs74WvvASvfDPhTDhti9Cqkf3skwd1l5FvHU2fJtdQWAmqIUR9SCi7EeUayHVQFc+KbRasW0KbMPANC+Mx6OUohJAriaJFKzMmIRS8cVH6pRD8ExI2IKYLYhbcNNKG9MQnChERApiliBuC2IWZzfk60lCJTfCtutehmGeoxHA0yOncR+wXgixGhgCbgNec8o23wTeCPwCeDnwn49bPqM0oi+KqcNw5MfaA2hbp93pjo16PGizZlxJ8KugSnNc6zkNNUrqi9P0wE2f5upHSjfWjRTKTAwdJVEbJtl1OZZhcNGezxKrjaGAQWs1t5b+lA9uHOe/M0a3F+Kas/9+KCVOVKMjKhHFBih1PoNx0UE6neLSnvTTd6DPTOhqtV7sJg8DSpdBz0FfJkYt6KBQC8nU8wzc+bsUBm5iatNrQAhescnhZEnypf0BXSmTF/fvQ00fIEj2ESa6Z5odY46JYcCOYzm29aVpTzUWb8PUv/3wQ2AtPuebq98BJ+7V1vXz/2Lm9+5Oe+wdKc6QhrI8hF/Em3yUasd2MGzecPUqfn54kn/6xSB/+LxNC358yrM5kavS33IWQ5r8ig6VFoZ1OAg04bnn6E2EdRjbDScf1LfR3fr9b/wP/XlX/5bO08UaZBBvm+8ZXvSyebmHqh9SrIWURkMCOT2Tb7ANoxFatc662nUuyr5iqibJ1dTMbVXG4JIui8PTER+7tzrzfNCwtba0m/z1zQlMAf+2z8c0oBbq6xL0bty8ShsPH7uvxq7x+Vporgl/cX2cbZ0Wtx/y+eFgQMIWJGxB0oGkLbis22Jbp0WhLjmYkyQdQcoRje0axCMlQgYIGWDIAMIaQjW+a0bJAWYyJaoRgpvbN4Kas61CVoq/vB3hjRzFbwHfQ9fQfVYp9agQ4s+A+5VS3wQ+A3xBCHEQmEITy+ODTD+lV36N4s8/TUbU8QoHMcb3w+gj+nXLg7b10LFBE0l2xTnVnisF1TCiNrSbaPwAdv4wq8rHWC+1XMRxo4odlggNj0hYVJx2XlL4YxI2rIgHnGpwGWEdqzRKa0uG0qpbKSVXM+0rVrclWNmWeEpbQ2cNy9XHOdkNo7t02CreNrMoGwasakuwd6RAWXpU2rfRtu9LWNUJxi55B8Kw+O3LPMYqkk8+GHJFb5bOuMIun8QpHiV02wjSK4jcLK5lYsQED5/Is6VH0d1svEt06AU3qOh8y0JIdsJlb9a6VIM/hdV6NGzStUi4JvVA4tr6XJFOCrM2jTe5l1r7VjpSLi97Rh9fvu84L9peWDB3YQiBIQSj+Ror208pbZVSl4hXclAYani2zdxE22kGy6KQIeRP6HJjpeDLr9HhJmFoXa6LXwW9z5glnvXPPW036mGEH4ZUGgRRrofIxgImENiWwLVM4kvwHpRSjFcUB3MRa7Im3UmDf9tX5+8ePF1u5b+tt7mky8IzBUlHMJA2afHEzK070QhjCcE3Xp7CEAKlFH4ElVBRC5npjXnLdpeJqqISKKqh9lYqgaIj3uiDEppkxiuSwUBRDhTlAGK2YFunxb6JgD++6/R9fFZ7mQ9ddJJQwv/Y2U/KikjYiripiFuKlC157UpdtfZQziXEIG5KEpYiYSnipiRmKk7t4bH8U8KBjwOetPDU44XzKbnNPfojinf+NX6iF+wYiUSalAux2jjm9FGY2KctX9Ak0r5eX1DtG3Q1zakkUs0Rjh8gGD/EZHoTRnmczmPfwYwqKGEilGxYDhpSWNTcNspeN2+bfhMP1bq4rr3EO9ZNYTSaiMyoihnV8MMAv30bmQ3XUghNIqnY3JOatZJ/2SAjmNivq9birfNKYat+xO7hAnHLpPPgv9C278uUuy5n+Ip3oywPP1LsnYzY3mnNLGKGEBhBGSOoIu0YfmoVYbydUJlMVX02dqXob2mQRGUKTtwPyTN4GzKEr79dh9Ze+Y8zBDNdCTgwXiIbmx8Ss6qTBMk+6tn11ELJ27/4AG0Jh4+84mKMBRb6SCoKtYCr17ZhE+migfI4FIf1dwujUf59lrkrJWHyEJzcAUMPwshOfYybnsTeb2kvomf7grm6WiCpBhHlekixHlL1I2SjZMlszD23TeO8ai4eGQ+5+2TIgamIQ9OSfF3/du+41OMlGxwO5iIeGAlpiwlaPYMWT5B1FWlbYQltgQsVNe5l4/709W7mGSEQam6VlJrJtzQVDlSjgU8JAzAanxsiZOPWrIQMqtiyRtGHg2WXUmhQCg2KkU0psuiKKV4w4FMJBe/ZkaEUCIqhQTUUlEOBZypuv1nX+7zlZy0cLJ4env301VNsTAf806E4Pxz2SFiKD6/dyeaX/U8M69z7WM42PLVMGnMwdccnaL3rf532/FhqK8c3vJ6sWWfVgx8GYSCQiMifSYIpKwbt63USrjAClUmEPF0GW2JSc1qoxzqpue3U3TZqbht1t526lWaw6vJPgy08WvAYiPl89OIRBBIrrGCoiNCMUbMSnExcxMrV66gEkpRnsaUnMxMG+aWFUrrpbmyP7qGYs0BOVwL2jxbJxByyR79D585PUc+u5cSz/xI1J37/6YdqjFckf/DMGHbD4hWRj+mXUUIQJHupx7qZCPS0wlVtCW3NDT2gixkW6pJvYmQXfPO39dCmq34d0Bb4o8N5vZDOlWtRCqs6QT27jiC9kjv2jPJXdxzgd5+7gRs3ds7/XBlhhGUKuQnWxCt0WVV0qbetiWKxXpKFjl8z6fvl10LxpH4+MwB9l2pPYuU1i+Y7qn5EoRYwWfK1om+DIBzLwDGNJYWXIqk4lg85mIsaN8lvXGyyIQuf3x3xz3slq9KwIatYn9G3NWmIWXMasml4Bo28ozR0vlGaNspo3ExHJ5GNRsK5QQRKzBa4aIKJZq5rI6wjohoirGCEVYyghBlU9N9BVVdNKdnYiwbNCFDC0j0tQlfOPdYKK5obzGyrQ2lO43Q5XHbIBwblwKQqBeXQoBwZ3NqVJ+vC7SNpfj6ZoBwa/OnGI2z6lXdhWOceRHo65DSecqiuuI77e1+Ll27HjGqYURUrqlM1kxRrIdWwTjq9GUfV9ethFTPUie5yZj3x6UO4NW0dSMMljHcTJPsoJ1cyIbIUjVZEvBVjjvkVKSiFBhlbsnPa44N7Ome8j99ZN4YTFgCDmtuOMkx8J8NRey09HW2U/IgVrQlWt/+ShKMeC0LocJWdgOEHtYXd6CzPxm0GWuOcyFUxVr2AyGvFKRyZRxigezn+dW9Ivl7hvdfGSdhCTwaMOaAi7PIwTvEYntvK8RPdRGE3azrTGG3r4djdjT6cRczn7m2w8VbY9VU9JrZ1DYYBvRmPI5MVMnNJQwjCWCve9EGU6XLjpi6+9fAwn//FIFevbiFODcMvYlXHMWvTCCSOFIxUbdpWdmGdixxxcQT2fQeO/ARe+intJW97uSbA3mcs2oehFFSDiHw1YKJUpx5IhICYbZ5bl7pSM7F7GfqYSnskn3jY4PajAl82Uu19FAAAIABJREFUqoFMWJMxqCqbyInxkm0Gr7jExrIdVKPQpLnYV2YsfnNOZdIZKhwX2qeopr3N6hRmWMaIfIyoDkqeJg+lhEA6SaSbRRmmJgbDnMlpilM1qma/aPZgMpdXF5I7aX6hQCGoNqq9etoFPQhdITa3/LexzY1dcGPjrZXcnNzq44RlT2MOhg7v4eiP/xG7bdWCr0sFfhghlcK1TTKe3UiiNhPgQGUS6WYxLBOloFD1yVV8TKG7SwFqkWDntMd9uRj3T8XYlqnzexsn8CV840SKb55Mc2m2xB+sG6Ya6yKwUlhhmWq8jzGnn0iYrGiNs7U3/csbjnos1Etw8iEt/dJIkCsFRyZKTFUCMnPCQanjPyZIdM/0cnzvsM/H7quxJmvwwevitMZOX2iMoIwIKuRDi2TPRtasWo2ZO6I9ncUa/kBXFH3l9Vq/60Wf0OQgFbtO5PFsE+vUeL4MsaqT1Fs3s2ss4A++M8SbNknesFE3g0rL015sYyHIVwNWt8VpSz5GGEqGuvJr77fg+H36uYErtLx7auFmQtCeUSUMyVcCJkt1/FBhGgLPMrGsx1iMZNBoUAsQslESDhTqcM+Ux92jBg+MhHzg+StY25XhR4eKHJyosbYzyZqOJH3Z2AU3fpRShFIRhSGqXkbWi1i1Sex6DqEivXSbFlI4SGPW8xCzASqaLRzNpVIv12JmbTaFfmwYOvdkGuLxXrcXxS979dRTDoVaxGA1Tm8giVvGaT+8IZipXgkjyXiphkCQ8iySnoVjmZBow0CTy0Spjh9KXMvCEDBRN/nMkRZ2TnsEyiBhRlzeUuFZLdMM5X2+fLKDu6czJEzJi9faTGe3YIUVTFlnOruVit3KeL7KFavSPGNF6y9/OOpMcJN6ERx9ZCZBLoRgRVuCWlCkWo+IuSbIgNa9/4JdHiG/5leY3PRanrcmSYsn+POfVfmdH5b5yxsS9KbmE4e0tc5YKvQpn9jF0cm9rBhYhVWd1jpMbpJ5Sr4zAnVxuPJtcNdHYf93YeMLsAxBb0PIMB2ztZUbVjGCCqY/jVWdwpvcwxUt67muL82XDxg8b0Oa9vjpZJZwLI5OVYg5FvEz/f53fggOfF97EZe+XntAi5BFJKHih0xXfCZKPpFSmELg2SYxZ4HVT0UYQRUR1RuLa6O1znKRdhLfSaKsBD84VObbe3PsHy2jCMnEbC5f1Y4Rb0E6Ca7fnOL6s//FF9l3RRBJQqkII0mklL5uQx8zrGAFBRLhNBlZxjUFjmViZ+JYTg+WbWEZBlZjkZcSJAqlQCqFVPpxpNu7kY3nlVJEskFGUm8XSt2RHoSSqh9BWMeMqhhhBSusYYQVzKiGFVWwohp2VNX5yVDfG0FFG0BN4mqE0DSJmQ3vZvbx3NCaDrfp5+zIAF72WIftvLDsaTQgpeK2T93Jvcf15KuYEdHp+nS6Ec9oqfHc7gqhhGMVmw43ImlpV/1U7yMbswkixVS5zlTg8FA+gS8FL+svUI8Ef/RwF5ekS1yVzbM5WeZYPcGXhru5bypGzFQ8d6XBLStNEpbC8XP4doZiegN14TI0XeGylS1cs67jv0Y46mywQIK8Fkj2DBd0rN0yMPwSbXu+QObI7URuhoktb6K44ib2Tik+taPG+58do8U7c1ijUKmRoE63UydROIAdb3b5N2xRxWxwWim4+1NQmYAb/xjcDAEmByYqxCwLOyw0SisF0nRRpqPj6DLisLORt37f54YVNn941cLS6bUgIpKKTd1pPNvQsjZH7tIiittfBSueqfM+1RwMXLlgziOUiko9Ilf1mZpDFHHHWjB5LaI6RlBBKKmb0+IdRF5rY/9dioHBQ0NF7h+c4qXP6GNlW4KvPnCcew5PcdnKFi5b2cK6zuSCSf6zhVSKeiCphRGqsaBbpiDhmMRFQELU8KI8bj2HFWkpfNu0EU7swqlVR74uPsgP6Wq15n15XJc7B2Xd07LQnPtToDCIrBiRFUNaMaSwdXGMChv3UePWfE4/RkYzr52KcmoNsXfe/7h6Gsuk0cCxyQq3fuInlOoRMVPRHYtIGCHFAC5LTvHWnqMc9xP8+t7tAMQMSYcX0umGrE4EvHJAT4fbXbDZlY+zI5/gWEXH07cky/zvjUdAQGS4BE6ag9U0Xz/msWNcNwzdssLguSsEKVO790ZUo5xcSTmxgkogKdcDVrcnuGlz9zJhnIoFEuTFWsjekQJpz5lZBN3pg3Q8/HfEpvaSW/cyJi56C0rpssXpmuTwtOTS7sWd7+aC5ZZP0hqOk2rpIOaa2AstRvkT8KMPwopr4OLbQEnGi1Vy5QAvvvB8ERGUQVj8zfHVfGVfyN/ckmBj68IXf7Ue4ZWPs3byx5gHv6+b+FLd8Mzf0CKKCxyieiip+CFTZZ9CTZfD2obAsxcgioY3YUR1QCDtBEG8k8hrmemyHspV+fnhCR44mmPPcAGpdJnx/3jOeq5e0zZzbJcCqVRDW0oSSi3/YRiCtGfTErdJOQYxVcatjCIq41rNoTmnw46dn6hiWNdd84W5xHBC35fGmFfS6iS0OnSiSz924trbbMrhnPrYSej9cxK62VeI+eKKDQ8mCCPqoZw5BvWw4UUxpwBAKQwUNhJT6JtfHGfrTa9bJo1zwfnkNA6NlvirO/ZzaLzMnpECSsGaNo+rBhJc2SFx/EkOD08xVfEZr5mMBQ4jvkeLHfL+DcdQSvGqB7cQSMHmZIVnZgtc3hbQmooT2kki0+NIyeKbh0IeHIe4pXh+v8/z+3wSFihhEJpxIitBNdaJb2co1AI82yQTs7lmXfu8WP0yTkF5otGIp2cYjBfrDE6Uycad2QykkqSO/Se1ts0EyT6cwiCh18aHH7T4wWDA713p8dzVj7HgRBFifA9BFILlkXItMnGHuGPO76fZ9VU4+EO4/o+gdQ1+pDg0VsKzzUU7nY16kZKR4rafdtGfMvjYc+ILLryJkXvpvfvPUMJCrXoWxuYX6QqoOWQURIqKH83k1fxG95prGri2eZrh3fQmmlVIYbyDMNaBtJMoy0MpxYGxEu1Jl9aEw1fuO8YX7znGmo4El69s5fKVLWzoSp2zUaOUmlkYg0jq3gchSMcssjGHdMwmZpt4pkI0O9wLJ3Vzoek0xD+XEGmXkTY0RnbNkkLTa5gLN621yNKNW/Nxpn/B5t3HC5HUDb1RIywWyIZab5NYggjXz7Hu6v+GWMKEzWXSWAKOT1b4fw8N0d8SJ18NuP/oFPcemWKsWMc2Bdv7szxzVSvr2h3csIxTmyRWHcGUVQSKCJOdUw6r0xFJL4YyTAQKQ/ocKQj+7ajLg5MWcUvxvJUm169J4sRSSNMlMlzkHF2ZMJIU6yHdaY+YbdDfGmd91znKSPxXRL0IJ3fqRHAsw9GpMuNFf2GyVYoVP/otrFqOoY1v4J1Hn8WOMcVbL3Z51SbnjFayEVTwJncTOin8EAKpMASkYxaZmEPMNjHCGvzwfbpK6Yb3gGGSqwSczNcWHq/bgFmb5uvjfXz00QR/ck2M6wcsvKndpI/dgbRiTGx7GyKskTlyO8Od1xHLtLOmPYlAJ7FLtZBcOaDsh3okjBC4CyXhZ7wJH1BEdpIw3kXkZWc1m5RicLLMT/ZPcNfBcUYLdV531UpedfkA0xWfSKrHTsovgDCSFGrNknRB0rNoidukYzZxx8SzGgUmUjbEQMdme1JMW/eOLGX0cGVKd+8fuweG7p+dCe9l55NBkyDSvbrT/emCJ0AafZk05mAuaTShlOLYVIV7jkzx4PEctUDSEre5YlUrV65qpS3hYEYVbL+AV5/ACaabheOEZoyD5Tj/77Bi15hP3Da4YUM7167vWjCJ3XTJ/VCX/K1pjxN3Leqh5MrVrQsPDVrG6Qjr2nqs5oi8Ng5OlKn64elKtoCTP0Lnw39HbPJRqtn1fFi8mc8Or+IlGxx+4xnuGWPwVmkEp3SCqDEaVkqoByGR0kUT2bhNNrcLb8c/wLZXwrrnoBScmK5SrofEF5M7V1q59N0PpLgx+jlvjP0MpzKCND0KK25m/OJfn9nUDyVjhRqWaRC3TdTc3glrgfNFKYygiIgCaOQm5noTc7Hz+DR/95NDuoxZwCUDWZ69voOr1rQtWaq9FkSU/RDLEKxojdOadInb5vwRvFJqYc+mR3E+RCFD7U0cvweO36vzX6AbFweuhIFnag/Nyyzp/3nKYZk0zh3nSxpf23GcrpSHZTarKmZPZj+UPHIyzz1HpjgwWkQBazsSXLm6jYv79UAfIQOEihicjvje7lHdqeyY3LChg2ev75ipvlJKzej/Rw2FTUNoiyvl2mTjdmNWdI1tfZn/uqW1S8WcBLnvtrBvrEIUqZmphvOgFKkTP6b9kc9i1qf5YfplvG3sv/Puq2I8Z9UZwoFK4U3tA+nPTBGc+XoJtSBESsWKff9AvDhI/cb34SXbCJXi8HgJ09DzHGbHTzd0hISBCCoM3P1eTCIOxy7C2XAz+e6rkFaMKFKU/ZBCNSSUUod3Ikl3ypuVP1lgXw2/gJAhYbyLINU/4000MVqocdeBCTpSLtdv6ODIRJlP33WYZ69v55q1Sw+NKqUo1UPqoSTlWqxolAybj0kUDfXocw09VSY1QRy/F07cp6vdhAFdWzVJDDwT2taekwzQBUXzd27qRqk59wLmzy9v3s4yBLZMGueO8yGNiWKdO/ePYZsGVT+iFjSafFRTHsHQ070MQbEecv/gFPcOTjFR8nEtg4v7s2zuSXPv4BR7Zsiik2evb8cyxExST1d5K2KORdqzSHo2rmXgWsY8kirUAlriNlt6f0msoCcaSumqqvF91K0Uh3I+tUYH/UIwggqte/+FWusm7hDP5Mp2H2F7SIxFPQ4R1ohNPEp0hs5sURqn74G/pNh6ESc3vA6Amh8xUqwSty0Ekmz5CF25HaQrx7h/w7tQwqRjeid/PbqdH1dW87+uFKSdZhoUDGHgWAKrsTgopSjWAzpTHu2pOeEiJTH9IkKGBIneBlnM6ldNlur89OAEdx2YYN+oDtU8b0sXv3XT+nM61AuhGWKNpKIr7dHXEiPtWbPneFOuvTSmcwlLJQoZanHFY/dqj2LygH4+1qoJYsUz9ZCsM3XzLwXNgWxhXZfLzunsnrPRTIOHUrpqLUQhMYiURagEdSkIpEEgBZYJtpC4hsKak+C20P0ys+fhTAfJfAhgzU3LpHEuOB/SKNdDdhzLIaUi5dlYhtC115EeE1n1Q6q+pBJE+GFznoXi2FSVnSemeeRkAT+UxB2Ta9e1c9nKFtxGiMC1TNKeTcqzcG0D1zLPmDDUF1zAlavbnr5qtU8VNBLkgeEyWNCSI9mY/ZiyF133f4Qwd4w/Dd/MbTdcTPsCTYAAVmUCpzA4E6ZaCOnB75Id/C6jF/0a9bYtIKAycZz4yH1053fiBHlC02MqezEnep9HZGnPZbgieNfD/Ty7R/LGi87sbUZSUfID+rIxsjETs15EKEmQ7MVPDegmwcZ2piE4Olnmt7/0oA6FdiS4bn0H165rX1Si/WwxNwQ10BKnK+PNnsNBVecRSqNQGgcVaql6dwlEcexuOHjHGbyJdRcuSS1DLTUf1TXZzUw2TKK8DHUrRYhJKAWBgnoIdamoh1ALFHWp8KUusxVND6fRMGgKTf6Gwcy0wEjKhkx8wxFpeCOOCZ4pcC2Ba4JnCVwLbAGmofQkwvTSJi0uk8YSUQ8jJos+x6YqurzSMkk45mlJ0WZTUdCUfg4ichWf/SNFBlpidKQ9kq5FzLHwLOPcZB+A8VKNzd1pehYLNyzj3FAvwfBOZFDjeN1lLO+TjtlnNMiSQ3eR2fkPxP1J/oPrab3kVvpbU/hpPejLrOUaTVc2buEoRFWUs4g1K0O67/8IdmWMqY2votzzTDoe+iTe9CFyqfVMtV3GdGYzyjg9BPRPR9LcPpLhT6+U9GcfgziiiKA8RX/WxWlfTZDsR5ouhyfK3D84xf1Hc7iWwQdesg2lFP/+4BBXrm6dl8dbCpRSlOsRtTAi6ZqsbEvQmnCwkLNjj4sjDRVetG6YHT/3HEX+BOy7HfZ9V0u/x1pg4KoL5000vYemB9EscjUd8DJIN0PNjFOVNqXIZrqm9biiSM0zQppzxc3GzTKMC1Iq36ycalZRhY3mwiYc0+DqtW1LKnVeJo3zhFKKfDVgaLrKWKGuK2M8+5wX/3OFH0pK9ZBUzOKS/uz8BOEyzg9RAKO7UcVhRoIkx/N10p59xkE/IqwiHvoSK45/A1tEDIo+Prf2E9y2xWH9d1+L5RdmtlUIlGFx8qr3Ip0ULfu/hpfbrzt2G1a0UzyOQFHov4Fy1xXUzDjHK7aWZl/kQi+Fgt/e0cuaRJ13XRFfcCCVUBFWUAAEBa+XCdFOX0cLX77vOA8czTFV0cKa6zuTXLGqlduuGFhyD8VcRFJRrAVEStGRcunPxEhbdUSt0Jh5n4Pm6GMnvrT+ibAOg43mxZMPagt/4CrY9CuaLJZSbtuEjLSX0uzzQOkeilgLkZOmKjyq0qYYGkxXA0q1cJ6ar2uZONaFIYQLgclynevWdyxp3ViWETlPCCHIxh2ycYe1HRFjhRrHpqoEUUDcMc9v9OYcBJGWHQikRCkaVlqc7oy3TBgXGqYNPdsRbpqeif04rXEO53ySjr2orpKyYqjL38KetS/gwJGjPDAu+OmxgNdudZjc+mb2jZboj0dkrADTL2JWx1GmzimE8Q78oKy7eRt6TMW+azHCGukTP8YuDzOx5Y20JW3Gi3USi5xTSUvxyoE8nx1sZc/xUTav6Jmx0IUMscMiUgkOqj4ezHnk65IXbItzdKrMoyfzbOlNc/nKFi5d2UJL/MJMcqyHEaV6iGkI+jMG3U5ILBiG0VFtpQsB1nnOG588CHtvh4M/0CGtVC9c8auw4Xl6zslSoZT2eIKqJqB0H4HXQg2HqnLI1yT5SkApF+peEBFhGTrnmI3ZF4Rsn85Y9jTOAZFUTFd8jk9VyFV8LNMg5drnZGVEUukkexgh0FpW7SmH1oRLwjVxreX8xROC8gQM76QQGByYVjiWcda5o3qocC3BRFXy6m+UANjUanD9CpubsyfpMfLIhebFz0Fi+G5a93+V0Gtl/KK3MhRlqfnRovsQSvj9h3uQUvLxi4eQTgaFYkc+yf2FLLvGI6Yquu+hLxvjXTdvIIwkvozY0pO5YOdVxQ+p1HxSRo2VMZ8WOYUVltCmt730Rrsm/LLOU+z7Nozv0/mO1ddpr6L3kvOreArr2quQChVvpRzrIaeSjJb0TJDmVeyYOudom+JpRxBPhKexTBpLRLkeMlqoMTRdJZKKhGMteMFHUlELIuph1NDKMehIObQlXZLuwu9ZxhMEvwwjD1MtF9lXsBGweO/EIhgpSe48HvDjYwEHc1pv6OauEu/bnkctEEaaCyd/mI5HPouQIWObXscBY7WuzltgYVQK7p6M8bEDHVyVyfHHqw5Q9Tp4246V1KTBxo4Ym3qzbO5pmTcXvuKHCAEbulJLJg4lIyrlAlFlmlaRp8+pknJNndA9l8FPi36BgtFHdfjp8I8grEHrGk0U624+vx4KGep8lgwJzRilWC8TMslIxSCMJKYhiDlPnLHWNDynyrpLP1cJZh5X/QjDODUX0nxsYAowTaOROBenbaurq+A3b1i3TBrngieKNJoII8lU2edYrkKpFmIZBrYpqAVadtkUgrakQ1vCIdWQQ3i6WS+/1IgCGN9LfeoEh8ou9Uj3yiwFJwoRdx4PSVLl1a0HGBWtfHBXhhu7a1zfVSfjLDA1rpKj45HPEKsMsaP9RXzLuIm0Y3BtR4VIwfse7SLnm0wHBr6cJZNbVsBtGy1OFkN6nBqeCECAb2epeZ0EdorI1JLqZT/ENgUbulIzJbpnREOFl1oBvziKWZkg65m0pz0S8STY3oXpcahOayXevd+G6aNak2ntc2DTC/Vs9qVeJ0ppjyKoUVcGRbebEZlhMnBQCGzDIOFaFzQPUQ8jcuWAqYpPrjyXFHymyoF+XPbJV4MFhzKlPYu4YxE1FHSbyW45RzpEnsVSvaYjwQ/fdf1yTuOpDMs06Ex7dKY9irWAkXyNih8x0BInHbdP73ZdxlMLpg1dF+G6adaP7GGwbJGvKjLeY5fknor+tMlrt5qASzjdwdhYhdGqwUceTfPx3YrL23zaXMklrQHP76uxe9riN+/egMOf82H773nRxDc5Hk3wSeuNXNtRwRSQNCO6ElVa7IhEPEYiHmfXpOD7xxQSyWs2WgiRwgc9DljWSBX3I5QiMlxqsU4cp4Wpusvh8TJrO5OYCyzGItQDiazqJKI8SqVWBaAzk6FtZR8x98LkQgjrulT2wPd1T4UMoesiuO4PYe0Ni89hP6vPrqHqRaq+pGC2MKx6yJOEuknMNmmJXziDLVfxeWQoz8Mn8uwayjM0XT1tG0NAS9yhJeHQnnTY0JmkJeHQmnBoic/eZ+P2Wak9SKWQcyqmwkjNI5nmSODHG8uexjKW0URliujkQ5yYrjPmO2RizpKNXRGFeJOPIg2b/ZU4/znscueoix8JXjRQ5U3rKuTqgq8fi9PmSlqdkCvy32XD8LcoxnrZv/I1WLYLCqqxLupu20w5rlKKL++XfP+o5IZ+g9dvXrj5UMgAK6oiZIASBjmZwMn20tvdjTBtjKCMWcthVccxwgphpChFBthxelqTtCYcPcb1fKGklnU58AM4/GPtBcTbYN1z9JyPllVL/2wZElYKVOt1piOXYTqp2lkM27ugYad8NeCRIU0QDw/lOT6lS4djtsnW3jQbu1O0J9wGKdi0xLXQ4vlIwS8FyzmNJWCZNJZxXvArqJGdjIxPcKIWIx1zl9JcC4BZL+Lm9hK52bMOtcTGd9G25wuEwmbPureR67hywd4NpRRfOyi5/Yjk2l7Bm7cuXrLbeANmVKNaKZKNW3SkPK1LYJhUlEtVmXiWQW/GIxN3sC6Edzx9VBPFgR/oZj7L00nt9bfoMbNLERxsIKhVqJTyTFUlY1YnvtuB4aYuWNipVAt55GSDJE5MMzipScKzDbb0pNnWl2VbX4Z1ncmnTLktLJPGkrBMGss4b0QhTOxn6uRBDpU8kjHvsUedLgKncAyzMo58rGSuUhhBGWSIkCFtuz6NXZtk//q3M9J9wyJvUXzjsOQbhyRXdQt+9aIzqww031Osh7TELVzbQgCpmE1vJkbKXXgA0zmhmtPVTwd/oKufhAH9l8O658Kqa3XeYokIQkm5mCOXLzItPSrJFZiJDuLemRWJzwYVP+SRoQK7hqbZNZTn8HgZha6k2tyTYlt/lu19GdZ3Jh/3Xq3zwXKfxjKW8WTAtKBzM61uCvPYTg4VIhw3jmuf+2LhJ3vx/AIirKMWqjJSCiOsIGRA6LURJHpQlketfSstP//fbN7/SRLloxxe8zo90nMOhBC8ZK2JbcDXDkhCGfH27eaiXoJSCj/SA42G83XiTkhX2qM1rrXPlkwYYQ0Gf6Y9ihP36nBU23q46h2w7iYdiloigkhRrFSZzk1QqvrUY52I1ktw4lnS58lwU2WfH+0b4+eHJjg4VkIqsAzBpu4Ur75yBdv6MmzsTj2l1aWbeY7mKNonAsuexjKWcSZUc5SPPsCh8TI4GT13/Bxh+CW8qb1Ebnpe1ZEIKhhRndBr1WRxShI48ANiO/6e1SPfZarlYh7d9E5Ce+H+j+8fjfjSPsklHYLfvNjEbhBHUzdNSQVCkHBNUo1KHccyCENFJQiRClKeRWfKJRWzZ96/KGSkB14d+D4c+YlulEt0wvqbtVfRuvqcj1MTfiQp1UIm8wUqhWkt1ZJdhZXpPS9PBfTxuPfIFD/cM6p15hRs6EryjIEWtvVn2NS99NLkpUI2ktlBJPXi30h0R3JWmmTuxD6Y1UY0BNimMXNLOCZrO5PLMiLngmXSWMYFR1CldmInQyeHKPoCZRh4to1jWyihJayVMIDFZayt0hBOaZTIS+tKpbBK6GYJk73zVGdPRakWwL7buXjws9S8TnZt/UMq8f4Ft/3/7d17cFxXfcDx7+/u3fdLK8mSH/IjzsN23gkmBEKoEwcIDANtpzB06BAKbcoA0zIdpmSaKc20/wQYKAPTwhRKoZRp09ACKQUKSQgJbQN5OQ+wbCfBb0uyLVnSal/3cfrHvZI38q69tqXdlfX7zGj2cc9qf76+2t/ec885v4cPeHxjp8/lBXj/5RC3IWFHyIaFjeJ25LRnE8F8Ih8R6E3H6E/HSc/WDPddOP5SMJ9i9AU48mywBHk0HZSXvfSNsOqacx6KO5sojk1XKBYnsb0KkUQO6d2Il+w7rwmDxhheOjrDQztH+enuo0xXXfrSMW7dPMD2zYOsKSzu+m6u5wer23pBtT0/LNsKzC1KmIzaJGIR4nZQkiEaCevbSzgHQwTLYm6l29n5GQs5fF+ThlILyfegOEalUmayWGJsski5UsUyDqmIIW4BvoNl3JNLYYdL4BsB8Q2xid2Aj5fsCxYSPMOs8VkjkxVk9Hlu2PM5LL/GkcFtlFJrKKXWUEyspmjlcMP3/MWo8M/Dhiv6Lf765hSZ+Nl/iAfTHCaIjQ+Tm9xFYXo3sYndiFsJGqRXBMNkL3oDrH/dWU/u831ww5rYpZrLsWKN6XKVqDNFLCJY2ZW42SH82PmVUj1RqvHI7qM8tHOUvcdLRCPCazf2sX3zINes7VmwC9jGGMqOh+OdXJ0WTp4dxG2LZLj0UDIaIRGNEItYRO0gOcyv29MpmjSUWmTlmsfETI3Dk2WmKw6WCOm4TTwiYHzEeOGtD8YjUp0kefR53Hge/yxWY/V9w6+PzZCoHuOql75MfmoY26/ObXcjSarpIZzcEG52LU+VV/KZ3f2kCmu4Z1uOdPQMH0jGEC0eJDm+k8T4MInxncSnDwSbxKKU3UixZxO1/i2khq4hu2JN06G4jm/wPINrfFw3mKBWdQxVz6XqGhzKM0rBAAAR30lEQVTXm6tVLiKIWyFlykSjUZzcOtzUylMqCJ4N1/N5Yt8ED+0c5cl9E3i+4bLBDLdtGeTmS1ac88TNU/6dnk+p5uH6wZlZTzJGLhElHY9gR4IJvtGIRSxiLZl5Wpo0lGqjcs1jfKbK4RNlZmrBumLpuH1K/7g4JRITu4hUJnAT+WBtpQa8sCtjdgJX1fHYP14iE7dJ2RF6rUnytRHSpcPEiweJFQ8SLR4kWj429ztcYzFiDZBZsQ6TG6KWGaKWHcJJDRIrHiIxPjyXKCJOUIDJi2Yp926m0reFSu8WKj2Xzn2Iz5YAMEAhGSWTCEoRVx2fmutRC/vkJfyKHfTBB0tbnFz2wsISg+UUsbwqvp2hlluPe55dUL8+NsODYffTZDkoXnbLpgG2bxlkXe/5LfsOJ88myo4HBuJRi4Fsgr5MjEzc7uoRVa3SpKFUh5RqLuMzNY6ECcQSIR1eeAbAGOzSKPHxXTjGompncD2Dj5nr0ohFhGTMJh2zScYiRG3hxIzD4RMlCunm3UHilIjNHCY2fYDRI/s5dGA/m+0jbJAjWP6ps4Wr2bVBcujdTLn3cpzMmjN3CZng+ofrm7Cv/eQ6SaedRe+7QWEofJzUIE5mNX4sf85dUJNlh0d3H+XB4VFePjqDbQk3XNTLbVsGuX5d4by7n9zwbMLxgzXFCqkog7kEuQt0OSAdcqtUh6RiweikoUJqLoEcnihzvOhgxGAhQIFI/loK5f30useI53qJJ5JBt0Z4MfSU32vblGoexYrbtJvFRFNUey6h2nMJqbVwYq3L7T8rsTYNn72xSH/tENHSCE5qJZXezfjNikadjkAi1voII3FKRNwKxrKp5TfgpgbPuQvK8Xye2DvOw8Njc91PF69Ic+fNG/mNy1aQO8c65hCcTVQcn7LjYghGJQ3m4/Sl42QSdlcPvW0nPdNQqk1mqi6lmkcsrAcft4P0wcxRGP1VULshWTjtN++q6zM8MoWFtPzB/fSIy18+VmJF2uJTt6Salq1dUMYjUisinouXyFPLrg9mxp/DLHBjDLtGp3l4eIzH9hyjWHUppKJs2zTALZsGuKi/+eizVn73TNWj5gXdbvlklMFsgnwqGHF2oZ1NnI52Tym1lLg1GH8JThwI6mWfZj5C2fHYNTJNRFpPHM+Pudz9aIlCQvj0LWkG0ouTOMSrEalNY8TCyazGTa1qeZTYfKNTFR7ZNcbDw2McnqwQsy1eu7GPWzcNnPfoJ883TFcdPD+oOLgqnyS7zM8mNGkotRSVxoOzDrcCqULTeQ9lx2N4ZBrbkpZrsvzqmMuf/7REJir84bUJrhu0ycUX4Jt0uASK5Vbwo6ngrCLZhzmH0q6lmsv/vnich4ZHeeFwUEr3ytU5bt08wE2X9J93xUzH85muOIjAmp4Uq3uSJM+iq+1C1tVJQ0R6gfuADcBe4F3GmIkG7X4I3Aj8zBjztlZ+tyYNteR5LkzsDc48Yungp4FyLUwckdYTx+5xj794tMR4JbjovqnX4lUrbV610mZLf/MlSBryXSK1acT4OMkVuJkhvPjZX9j2fMOzB07w8K4x/u/l49Rcn9X5BLduHmDbpgEGc+c+BHdWxfHCuiIW6/tSDGQTJwcmKKD7k8angHFjzL0ichdQMMZ8vEG77UAK+CNNGmrZqUzB2C+hUoRUT8MhqaVa0FV1NonD8w27xj2eGvF4csRl+LiHbyBlw7WD9lwSWZ2ZN+nMd7DcKuLVgkmLVoRadj1uagBjn92sas837Ds+wyO7j/LTXUcZL9XIxG1uvrSfWzcPsGkwuyDXE2aqLhXXJR2zWd+Xpi8T76pVabtJtyeNXcA2Y8wREVkFPGKM2dSk7TbgY5o01LLk+zB5AI7thkgMErlTmswmjmjEOqdFFYs1w44xl6dGXJ484jIyE3wmrErB1gGfrSsM1/f7pFJJvHgPXrwHP5rCt9NNL2wbY5iqBCWRRyYrwW34MzpV4eh0Fd8Ey2JsXV/g1s0DvHpD74JcU/CNYbri4ng+vZkY63tT5JPRZXVR+1x0e9I4YYzpCe8LMDH7uEHbbZwhaYjIncCdAOvWrXvVvn37Fj5opTqpNgNHh2HmWFAz27Jfsc7VTM1l90jx3BKH8RC3iuVVEWM4NAO/OGrzxLEoO8Zcyo7BCuuMX7e2h+vXFbh0MIvr+4xOVU9JDKNTFUanqsFEuDo9yWCew2Auwcp8glX5BK/e0Ev+PIbJ1putXOcbw6p8gjWFFJmzrPm+nHU8aYjIg8DKBpvuBr5enyREZMIYU2jye7ahZxpKBYtCTR2BE3uD2ua+GyxDHio5Hi+OFYnbkVOW+TCYuSQzuyYWvgcISOTkGUQsix9NYiLBBELX89k1Os0zB06wY/8J9oxN45ugzkTN81/xHjHbYmUuwcpcgsFcnJX5MEHkEgxkE4t2wbnm+kxXHSKWsK6QYjCfaLmrTp3U8cl9xpjbmm0TkVERWVXXPTW2WHEodcEQgfzq4GeWCT/8jU/K+GwYqvDc/nFSUYtERAD/5PpXvof4DmI8jFhBgrBTQYJo0nVjRyyuWJ3nitV5fu8165muODx3cJKdR6bIJuy5pDCYT9DT5i6giuNRrLokohabBrP0Z+PLeshsu3Tq3O0B4A7g3vD2ux2KQ6mlTSQoGhXKRRNcdXGaZ/ZP4EXsBf/GnU1EuemSfm66pH9Bf+/ZqDgexZpLKhrhyjU5+tLxJbMo4IWgU2n5XuCNIrIHuC18jIhsFZGvzDYSkceA+4HtInJQRN7ckWiVWkLyySjXrS0wU3Oput6ZX7BElGsex4pVBLh6TZ5Xb+hlRTahCaPNOnKmYYw5Dmxv8PyTwB/UPb65nXEpdaHIp4LE8cyBYPpTu6vRLaRSzaXsuGQSUa5Z20MhpSOhOkmHFih1gcqnoly7todn9p9AErLkJrOVasFaXflUlMsGC/RosugKmjSUuoD1pGJcu7aHHQdOkEtEl0TimKm6lB2PnlSUTSuzOseiy2jSUOoCV0jHuGYoz7MHJ8kno107wqhYdak4Lr3pOFtW5cinFmb+hlpYmjSUWgZ6M3GuHsrzXJcljtmlySuuR18mxuWrcws22U8tDk0aSi0TfZk4V63J8dyhSXqSsY4mjqrrUa4F1f9WZGNc0Zcjl9BksRRo0lBqGenPJrh6DQyPTON6BgTikQiJqLWoda4dz6dcVzo1E7dZ25uiLxMjq8liSdGkodQy059NcFMmTtnxmKl6jM9UGZ+pUS07IGBbFqlY5LzORDzfUK55VD0PDMSjQenU3nScdDyypIcAL3eaNJRahkRkrpb5imywzlTF8ZipukyUaowXa0xVHASwJFh2PW5bTUcx+cZQcby5RQpty6I/E6MvkyGbWPiZ6apzNGkopQBIRCMkohH6MnEYCBYCnKm6TJYdjhdrjJdqAEREiNsRRIJE4xmDJUIhHWN9X4psYvnV115ONGkopRqK2RYxO0YhHWNDfxrX85mpeUxXHI4Xg3oYF/WkySWjpGO2FjdaJjRpKKVaYkcs8kmLfDLKUCHV6XBUh3THYG2llFJLgiYNpZRSLdOkoZRSqmWaNJRSSrVMk4ZSSqmWadJQSinVMk0aSimlWqZJQymlVMvEGNPpGBaUiBwF9p3Hr+gHji1QOItJ41xYSyVOWDqxapwLbzFjXW+MWXGmRhdc0jhfIvKkMWZrp+M4E41zYS2VOGHpxKpxLrxuiFW7p5RSSrVMk4ZSSqmWadI41d93OoAWaZwLa6nECUsnVo1z4XU8Vr2moZRSqmV6pqGUUqplyzJpiMjtIrJLRF4UkbsabI+LyH3h9p+LyIb2RwkislZEfiIivxKRX4rInzRos01EJkVkR/jziQ7FuldEng9jeLLBdhGRz4f79DkRub4DMW6q2087RGRKRD46r03H9qeIfFVExkTkhbrnekXkxyKyJ7wtNHntHWGbPSJyRwfi/LSIDIf/t98WkZ4mrz3tcdKGOO8RkUN1/79vbfLa035GtCnW++ri3CsiO5q8tm37FABjzLL6ASLAS8BGIAY8C1w+r82HgC+F998N3NehWFcB14f3s8DuBrFuA77XBft1L9B/mu1vBX4ACHAj8PMuOA5GCMamd8X+BN4AXA+8UPfcp4C7wvt3AZ9s8Lpe4OXwthDeL7Q5zjcBdnj/k43ibOU4aUOc9wAfa+HYOO1nRDtinbf9M8AnOr1PjTHL8kzjBuBFY8zLxpga8K/AO+a1eQfw9fD+t4Dt0oGCx8aYI8aYp8P708BOYE2741gg7wD+yQQeB3pEZFUH49kOvGSMOZ+JoAvKGPMoMD7v6fpj8evAbzZ46ZuBHxtjxo0xE8CPgdvbGacx5kfGGDd8+DgwtFjv36om+7MVrXxGLKjTxRp+9rwL+JfFjKFVyzFprAEO1D0+yKkfxHNtwj+ESaCvLdE1EXaRXQf8vMHm14rIsyLyAxG5oq2BnWSAH4nIUyJyZ4Ptrez3dno3zf8Iu2F/zho0xhwJ748Agw3adNu+fT/BWWUjZzpO2uEjYTfaV5t093Xb/rwZGDXG7Gmyva37dDkmjSVHRDLAvwMfNcZMzdv8NEEXyzXAF4DvtDu+0OuNMdcDbwE+LCJv6FAcZyQiMeDtwP0NNnfL/jyFCfoiunq4o4jcDbjAN5s06fRx8kXgYuBa4AhBt0+3+11Of5bR1n26HJPGIWBt3eOh8LmGbUTEBvLA8bZEN4+IRAkSxjeNMf8xf7sxZsoYUwzvfx+Iikh/m8PEGHMovB0Dvk1wil+vlf3eLm8BnjbGjM7f0C37s87obDdeeDvWoE1X7FsReR/wNuA9YYI7RQvHyaIyxowaYzxjjA98ucn7d8X+hLnPn98G7mvWpt37dDkmjSeAS0XkovAb57uBB+a1eQCYHYHyO8DDzf4IFlPYl/kPwE5jzGebtFk5e71FRG4g+D9ta4ITkbSIZGfvE1wUfWFesweA94ajqG4EJuu6Xdqt6Te3btif89Qfi3cA323Q5r+BN4lIIexueVP4XNuIyO3AnwFvN8aUmrRp5ThZVPOuo/1Wk/dv5TOiXW4Dho0xBxtt7Mg+bdcV9276IRjJs5tghMTd4XN/RXDAAyQIui5eBH4BbOxQnK8n6I54DtgR/rwV+CDwwbDNR4BfEozweBx4XQfi3Bi+/7NhLLP7tD5OAf423OfPA1s7tE/TBEkgX/dcV+xPgkR2BHAI+tE/QHAt7SFgD/Ag0Bu23Qp8pe617w+P1xeB3+9AnC8SXAeYPU5nRx+uBr5/uuOkzXF+Izz+niNIBKvmxxk+PuUzot2xhs9/bfbYrGvbsX1qjNEZ4UoppVq3HLunlFJKnSNNGkoppVqmSUMppVTLNGkopZRqmSYNpZRSLdOkoVQdEekRkQ+F91eLyLc6FMdWEfn8GdrMxapUu+iQW6XqhGt8fc8Yc2WHQzmjpRSrunDomYZSr3QvcHFYm+D+2foGIvI+EflOWNNir4h8RET+VESeEZHHRaQ3bHexiPwwXDzuMRHZHD7/NRH5kog8KSK7ReRt4fMJEfnHsB7CMyJyS/j8NhH5Xnj/nnBxvUdE5GUR+eMGsX66zftJLVN2pwNQqsvcBVxpjLl29pt83bYrCVYaThDMgP64MeY6Efkb4L3A5whqOH/QGLNHRF4D/B1wa/j6DQTrAl0M/ERELgE+TLAW4VVhgvmRiFzWIK7NwC0EdVV2icgX62NdsH+9UmegSUOp1v3EBHVNpkVkEvjP8PnngavD1YhfB9xfV34lXvf6fzPBQnl7RORlgkTweoLVdDHGDIvIPqBR0vgvY0wVqIrIGI2XSFdq0WnSUKp11br7ft1jn+BvyQJOnOab//wLiGdzQbH+vT30b1d1iF7TUOqVpgm6gM6aCWqd/FpE3glzddGvqWvyThGxRORigoXmdgGPAe8J218GrAufX9RYlTpXmjSUqmOMOQ78T3gB/FwuLr8H+ICIzK46Wl8mdD/Bqsk/ILjuUSG45mGJyPMENRPeF3ZDnVWseiFctYsOuVWqDUTkawTDYzsy70OphaJnGkoppVqmZxpKKaVapmcaSimlWqZJQymlVMs0aSillGqZJg2llFIt06ShlFKqZZo0lFJKtez/AV5xllVPtc0qAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lineplot(x=\"timepoint\", y=\"signal\",\r\n",
    "             hue=\"region\", style=\"event\",\r\n",
    "             data=fmri)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "py35-paddle1.2.0"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
